Wallis and Futuna
i=1
station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
[2021-11-02 09:12:37] Performing annual aggregation...
[2021-11-02 09:12:37] Done.
[2021-11-02 09:12:37] - Computing climatology...
[2021-11-02 09:12:37] - Done.
index.obs <- c(index.obs, index.obs.rv20max)
index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
[2021-11-02 09:12:37] Performing annual aggregation...
[2021-11-02 09:12:37] Done.
[2021-11-02 09:12:37] - Computing climatology...
[2021-11-02 09:12:37] - Done.
index.trmm <- c(index.trmm, index.trmm.rv20max)
WT1
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))
station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
[2021-11-02 09:12:42] Performing annual aggregation...
[2021-11-02 09:12:42] Done.
[2021-11-02 09:12:42] - Computing climatology...
[2021-11-02 09:12:42] - Done.
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)
index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
[2021-11-02 09:12:42] Performing annual aggregation...
[2021-11-02 09:12:42] Done.
[2021-11-02 09:12:42] - Computing climatology...
[2021-11-02 09:12:42] - Done.
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")
station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "pqm",cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:12:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:46] Number of windows considered: 1...
[2021-11-02 09:12:46] Bias-correcting 1 members separately...
[2021-11-02 09:12:46] Done.
Validation 2, 20 remaining
[2021-11-02 09:12:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:47] Number of windows considered: 1...
[2021-11-02 09:12:47] Bias-correcting 1 members separately...
[2021-11-02 09:12:47] Done.
Validation 3, 19 remaining
[2021-11-02 09:12:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:48] Number of windows considered: 1...
[2021-11-02 09:12:48] Bias-correcting 1 members separately...
[2021-11-02 09:12:48] Done.
Validation 4, 18 remaining
[2021-11-02 09:12:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:48] Number of windows considered: 1...
[2021-11-02 09:12:48] Bias-correcting 1 members separately...
[2021-11-02 09:12:48] Done.
Validation 5, 17 remaining
[2021-11-02 09:12:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:49] Number of windows considered: 1...
[2021-11-02 09:12:49] Bias-correcting 1 members separately...
[2021-11-02 09:12:49] Done.
Validation 6, 16 remaining
[2021-11-02 09:12:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:50] Number of windows considered: 1...
[2021-11-02 09:12:50] Bias-correcting 1 members separately...
[2021-11-02 09:12:50] Done.
Validation 7, 15 remaining
[2021-11-02 09:12:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:50] Number of windows considered: 1...
[2021-11-02 09:12:50] Bias-correcting 1 members separately...
[2021-11-02 09:12:50] Done.
Validation 8, 14 remaining
[2021-11-02 09:12:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:51] Number of windows considered: 1...
[2021-11-02 09:12:51] Bias-correcting 1 members separately...
[2021-11-02 09:12:51] Done.
Validation 9, 13 remaining
[2021-11-02 09:12:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:52] Number of windows considered: 1...
[2021-11-02 09:12:52] Bias-correcting 1 members separately...
[2021-11-02 09:12:52] Done.
Validation 10, 12 remaining
[2021-11-02 09:12:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:52] Number of windows considered: 1...
[2021-11-02 09:12:52] Bias-correcting 1 members separately...
[2021-11-02 09:12:52] Done.
Validation 11, 11 remaining
[2021-11-02 09:12:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:53] Number of windows considered: 1...
[2021-11-02 09:12:53] Bias-correcting 1 members separately...
[2021-11-02 09:12:53] Done.
Validation 12, 10 remaining
[2021-11-02 09:12:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:53] Number of windows considered: 1...
[2021-11-02 09:12:53] Bias-correcting 1 members separately...
[2021-11-02 09:12:53] Done.
Validation 13, 9 remaining
[2021-11-02 09:12:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:54] Number of windows considered: 1...
[2021-11-02 09:12:54] Bias-correcting 1 members separately...
[2021-11-02 09:12:54] Done.
Validation 14, 8 remaining
[2021-11-02 09:12:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:55] Number of windows considered: 1...
[2021-11-02 09:12:55] Bias-correcting 1 members separately...
[2021-11-02 09:12:55] Done.
Validation 15, 7 remaining
[2021-11-02 09:12:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:55] Number of windows considered: 1...
[2021-11-02 09:12:55] Bias-correcting 1 members separately...
[2021-11-02 09:12:55] Done.
Validation 16, 6 remaining
[2021-11-02 09:12:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:56] Number of windows considered: 1...
[2021-11-02 09:12:56] Bias-correcting 1 members separately...
[2021-11-02 09:12:56] Done.
Validation 17, 5 remaining
[2021-11-02 09:12:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:57] Number of windows considered: 1...
[2021-11-02 09:12:57] Bias-correcting 1 members separately...
[2021-11-02 09:12:57] Done.
Validation 18, 4 remaining
[2021-11-02 09:12:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:57] Number of windows considered: 1...
[2021-11-02 09:12:57] Bias-correcting 1 members separately...
[2021-11-02 09:12:57] Done.
Validation 19, 3 remaining
[2021-11-02 09:12:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:58] Number of windows considered: 1...
[2021-11-02 09:12:58] Bias-correcting 1 members separately...
[2021-11-02 09:12:58] Done.
Validation 20, 2 remaining
[2021-11-02 09:12:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:58] Number of windows considered: 1...
[2021-11-02 09:12:58] Bias-correcting 1 members separately...
[2021-11-02 09:12:58] Done.
Validation 21, 1 remaining
[2021-11-02 09:12:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:12:59] Number of windows considered: 1...
[2021-11-02 09:12:59] Bias-correcting 1 members separately...
[2021-11-02 09:12:59] Done.
Validation 22, 0 remaining
[2021-11-02 09:13:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:00] Number of windows considered: 1...
[2021-11-02 09:13:00] Bias-correcting 1 members separately...
[2021-11-02 09:13:00] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-11-02 09:13:00] Performing annual aggregation...
[2021-11-02 09:13:00] Done.
[2021-11-02 09:13:00] - Computing climatology...
[2021-11-02 09:13:00] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.pqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:13:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:10] Number of windows considered: 1...
[2021-11-02 09:13:10] Bias-correcting 1 members separately...
[2021-11-02 09:13:10] Done.
Validation 2, 20 remaining
[2021-11-02 09:13:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:10] Number of windows considered: 1...
[2021-11-02 09:13:10] Bias-correcting 1 members separately...
[2021-11-02 09:13:10] Done.
Validation 3, 19 remaining
[2021-11-02 09:13:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:11] Number of windows considered: 1...
[2021-11-02 09:13:11] Bias-correcting 1 members separately...
[2021-11-02 09:13:11] Done.
Validation 4, 18 remaining
[2021-11-02 09:13:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:12] Number of windows considered: 1...
[2021-11-02 09:13:12] Bias-correcting 1 members separately...
[2021-11-02 09:13:12] Done.
Validation 5, 17 remaining
[2021-11-02 09:13:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:13] Number of windows considered: 1...
[2021-11-02 09:13:13] Bias-correcting 1 members separately...
[2021-11-02 09:13:13] Done.
Validation 6, 16 remaining
[2021-11-02 09:13:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:13] Number of windows considered: 1...
[2021-11-02 09:13:13] Bias-correcting 1 members separately...
[2021-11-02 09:13:13] Done.
Validation 7, 15 remaining
[2021-11-02 09:13:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:14] Number of windows considered: 1...
[2021-11-02 09:13:14] Bias-correcting 1 members separately...
[2021-11-02 09:13:14] Done.
Validation 8, 14 remaining
[2021-11-02 09:13:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:15] Number of windows considered: 1...
[2021-11-02 09:13:15] Bias-correcting 1 members separately...
[2021-11-02 09:13:15] Done.
Validation 9, 13 remaining
[2021-11-02 09:13:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:16] Number of windows considered: 1...
[2021-11-02 09:13:16] Bias-correcting 1 members separately...
[2021-11-02 09:13:16] Done.
Validation 10, 12 remaining
[2021-11-02 09:13:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:16] Number of windows considered: 1...
[2021-11-02 09:13:16] Bias-correcting 1 members separately...
[2021-11-02 09:13:16] Done.
Validation 11, 11 remaining
[2021-11-02 09:13:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:17] Number of windows considered: 1...
[2021-11-02 09:13:17] Bias-correcting 1 members separately...
[2021-11-02 09:13:17] Done.
Validation 12, 10 remaining
[2021-11-02 09:13:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:18] Number of windows considered: 1...
[2021-11-02 09:13:18] Bias-correcting 1 members separately...
[2021-11-02 09:13:18] Done.
Validation 13, 9 remaining
[2021-11-02 09:13:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:19] Number of windows considered: 1...
[2021-11-02 09:13:19] Bias-correcting 1 members separately...
[2021-11-02 09:13:19] Done.
Validation 14, 8 remaining
[2021-11-02 09:13:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:19] Number of windows considered: 1...
[2021-11-02 09:13:19] Bias-correcting 1 members separately...
[2021-11-02 09:13:20] Done.
Validation 15, 7 remaining
[2021-11-02 09:13:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:20] Number of windows considered: 1...
[2021-11-02 09:13:20] Bias-correcting 1 members separately...
[2021-11-02 09:13:20] Done.
Validation 16, 6 remaining
[2021-11-02 09:13:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:21] Number of windows considered: 1...
[2021-11-02 09:13:21] Bias-correcting 1 members separately...
[2021-11-02 09:13:21] Done.
Validation 17, 5 remaining
[2021-11-02 09:13:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:22] Number of windows considered: 1...
[2021-11-02 09:13:22] Bias-correcting 1 members separately...
[2021-11-02 09:13:22] Done.
Validation 18, 4 remaining
[2021-11-02 09:13:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:22] Number of windows considered: 1...
[2021-11-02 09:13:22] Bias-correcting 1 members separately...
[2021-11-02 09:13:23] Done.
Validation 19, 3 remaining
[2021-11-02 09:13:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:23] Number of windows considered: 1...
[2021-11-02 09:13:23] Bias-correcting 1 members separately...
[2021-11-02 09:13:23] Done.
Validation 20, 2 remaining
[2021-11-02 09:13:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:24] Number of windows considered: 1...
[2021-11-02 09:13:24] Bias-correcting 1 members separately...
[2021-11-02 09:13:24] Done.
Validation 21, 1 remaining
[2021-11-02 09:13:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:25] Number of windows considered: 1...
[2021-11-02 09:13:25] Bias-correcting 1 members separately...
[2021-11-02 09:13:25] Done.
Validation 22, 0 remaining
[2021-11-02 09:13:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:26] Number of windows considered: 1...
[2021-11-02 09:13:26] Bias-correcting 1 members separately...
[2021-11-02 09:13:26] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-11-02 09:13:26] Performing annual aggregation...
[2021-11-02 09:13:26] Done.
[2021-11-02 09:13:26] - Computing climatology...
[2021-11-02 09:13:26] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.eqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:13:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:35] Number of windows considered: 1...
[2021-11-02 09:13:35] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:13:35] Done.
Validation 2, 20 remaining
[2021-11-02 09:13:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:36] Number of windows considered: 1...
[2021-11-02 09:13:36] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:36] Done.
Validation 3, 19 remaining
[2021-11-02 09:13:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:37] Number of windows considered: 1...
[2021-11-02 09:13:37] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:37] Done.
Validation 4, 18 remaining
[2021-11-02 09:13:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:38] Number of windows considered: 1...
[2021-11-02 09:13:38] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 09:13:38] Done.
Validation 5, 17 remaining
[2021-11-02 09:13:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:39] Number of windows considered: 1...
[2021-11-02 09:13:39] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:39] Done.
Validation 6, 16 remaining
[2021-11-02 09:13:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:39] Number of windows considered: 1...
[2021-11-02 09:13:39] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 09:13:39] Done.
Validation 7, 15 remaining
[2021-11-02 09:13:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:40] Number of windows considered: 1...
[2021-11-02 09:13:40] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 09:13:40] Done.
Validation 8, 14 remaining
[2021-11-02 09:13:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:41] Number of windows considered: 1...
[2021-11-02 09:13:41] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:41] Done.
Validation 9, 13 remaining
[2021-11-02 09:13:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:41] Number of windows considered: 1...
[2021-11-02 09:13:41] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:41] Done.
Validation 10, 12 remaining
[2021-11-02 09:13:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:42] Number of windows considered: 1...
[2021-11-02 09:13:42] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:13:42] Done.
Validation 11, 11 remaining
[2021-11-02 09:13:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:43] Number of windows considered: 1...
[2021-11-02 09:13:43] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:43] Done.
Validation 12, 10 remaining
[2021-11-02 09:13:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:43] Number of windows considered: 1...
[2021-11-02 09:13:43] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:44] Done.
Validation 13, 9 remaining
[2021-11-02 09:13:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:44] Number of windows considered: 1...
[2021-11-02 09:13:44] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:44] Done.
Validation 14, 8 remaining
[2021-11-02 09:13:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:45] Number of windows considered: 1...
[2021-11-02 09:13:45] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:45] Done.
Validation 15, 7 remaining
[2021-11-02 09:13:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:46] Number of windows considered: 1...
[2021-11-02 09:13:46] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:46] Done.
Validation 16, 6 remaining
[2021-11-02 09:13:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:46] Number of windows considered: 1...
[2021-11-02 09:13:46] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:46] Done.
Validation 17, 5 remaining
[2021-11-02 09:13:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:47] Number of windows considered: 1...
[2021-11-02 09:13:47] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:47] Done.
Validation 18, 4 remaining
[2021-11-02 09:13:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:48] Number of windows considered: 1...
[2021-11-02 09:13:48] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:48] Done.
Validation 19, 3 remaining
[2021-11-02 09:13:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:48] Number of windows considered: 1...
[2021-11-02 09:13:48] Bias-correcting 1 members separately...
[2021-11-02 09:13:48] Done.
Validation 20, 2 remaining
[2021-11-02 09:13:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:49] Number of windows considered: 1...
[2021-11-02 09:13:49] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:49] Done.
Validation 21, 1 remaining
[2021-11-02 09:13:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:50] Number of windows considered: 1...
[2021-11-02 09:13:50] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:50] Done.
Validation 22, 0 remaining
[2021-11-02 09:13:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:13:51] Number of windows considered: 1...
[2021-11-02 09:13:51] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:13:51] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-11-02 09:13:51] Performing annual aggregation...
[2021-11-02 09:13:51] Done.
[2021-11-02 09:13:51] - Computing climatology...
[2021-11-02 09:13:51] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:14:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:48] Number of windows considered: 1...
[2021-11-02 09:14:48] Bias-correcting 1 members separately...
[2021-11-02 09:14:48] Done.
Validation 2, 20 remaining
[2021-11-02 09:14:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:48] Number of windows considered: 1...
[2021-11-02 09:14:48] Bias-correcting 1 members separately...
[2021-11-02 09:14:48] Done.
Validation 3, 19 remaining
[2021-11-02 09:14:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:49] Number of windows considered: 1...
[2021-11-02 09:14:49] Bias-correcting 1 members separately...
[2021-11-02 09:14:49] Done.
Validation 4, 18 remaining
[2021-11-02 09:14:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:50] Number of windows considered: 1...
[2021-11-02 09:14:50] Bias-correcting 1 members separately...
[2021-11-02 09:14:50] Done.
Validation 5, 17 remaining
[2021-11-02 09:14:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:51] Number of windows considered: 1...
[2021-11-02 09:14:51] Bias-correcting 1 members separately...
[2021-11-02 09:14:51] Done.
Validation 6, 16 remaining
[2021-11-02 09:14:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:51] Number of windows considered: 1...
[2021-11-02 09:14:51] Bias-correcting 1 members separately...
[2021-11-02 09:14:51] Done.
Validation 7, 15 remaining
[2021-11-02 09:14:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:52] Number of windows considered: 1...
[2021-11-02 09:14:52] Bias-correcting 1 members separately...
[2021-11-02 09:14:52] Done.
Validation 8, 14 remaining
[2021-11-02 09:14:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:53] Number of windows considered: 1...
[2021-11-02 09:14:53] Bias-correcting 1 members separately...
[2021-11-02 09:14:53] Done.
Validation 9, 13 remaining
[2021-11-02 09:14:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:53] Number of windows considered: 1...
[2021-11-02 09:14:53] Bias-correcting 1 members separately...
[2021-11-02 09:14:54] Done.
Validation 10, 12 remaining
[2021-11-02 09:14:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:54] Number of windows considered: 1...
[2021-11-02 09:14:54] Bias-correcting 1 members separately...
[2021-11-02 09:14:54] Done.
Validation 11, 11 remaining
[2021-11-02 09:14:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:55] Number of windows considered: 1...
[2021-11-02 09:14:55] Bias-correcting 1 members separately...
[2021-11-02 09:14:55] Done.
Validation 12, 10 remaining
[2021-11-02 09:14:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:56] Number of windows considered: 1...
[2021-11-02 09:14:56] Bias-correcting 1 members separately...
[2021-11-02 09:14:56] Done.
Validation 13, 9 remaining
[2021-11-02 09:14:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:57] Number of windows considered: 1...
[2021-11-02 09:14:57] Bias-correcting 1 members separately...
[2021-11-02 09:14:57] Done.
Validation 14, 8 remaining
[2021-11-02 09:14:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:57] Number of windows considered: 1...
[2021-11-02 09:14:57] Bias-correcting 1 members separately...
[2021-11-02 09:14:57] Done.
Validation 15, 7 remaining
[2021-11-02 09:14:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:58] Number of windows considered: 1...
[2021-11-02 09:14:58] Bias-correcting 1 members separately...
[2021-11-02 09:14:58] Done.
Validation 16, 6 remaining
[2021-11-02 09:14:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:14:59] Number of windows considered: 1...
[2021-11-02 09:14:59] Bias-correcting 1 members separately...
[2021-11-02 09:14:59] Done.
Validation 17, 5 remaining
[2021-11-02 09:15:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:15:00] Number of windows considered: 1...
[2021-11-02 09:15:00] Bias-correcting 1 members separately...
[2021-11-02 09:15:00] Done.
Validation 18, 4 remaining
[2021-11-02 09:15:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:15:00] Number of windows considered: 1...
[2021-11-02 09:15:00] Bias-correcting 1 members separately...
[2021-11-02 09:15:00] Done.
Validation 19, 3 remaining
[2021-11-02 09:15:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:15:01] Number of windows considered: 1...
[2021-11-02 09:15:01] Bias-correcting 1 members separately...
[2021-11-02 09:15:01] Done.
Validation 20, 2 remaining
[2021-11-02 09:15:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:15:02] Number of windows considered: 1...
[2021-11-02 09:15:02] Bias-correcting 1 members separately...
[2021-11-02 09:15:02] Done.
Validation 21, 1 remaining
[2021-11-02 09:15:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:15:03] Number of windows considered: 1...
[2021-11-02 09:15:03] Bias-correcting 1 members separately...
[2021-11-02 09:15:03] Done.
Validation 22, 0 remaining
[2021-11-02 09:15:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:15:03] Number of windows considered: 1...
[2021-11-02 09:15:03] Bias-correcting 1 members separately...
[2021-11-02 09:15:03] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-11-02 09:15:04] Performing annual aggregation...
[2021-11-02 09:15:04] Done.
[2021-11-02 09:15:04] - Computing climatology...
[2021-11-02 09:15:04] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm2.cl1 <- index.cal.station.cl1
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i]))
}
normalization <- function(measure){
measure.norm <- c()
#measure must be a vector with the value of a certain measure of different calibrations
for (i in c(1:length(measure))) {
measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
}
return(measure.norm)
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
scores.st1.wt1 <- scores
WT2
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))
station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
[2021-11-02 09:16:41] Performing annual aggregation...
[2021-11-02 09:16:41] Done.
[2021-11-02 09:16:41] - Computing climatology...
[2021-11-02 09:16:41] - Done.
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)
index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
[2021-11-02 09:16:41] Performing annual aggregation...
[2021-11-02 09:16:41] Done.
[2021-11-02 09:16:41] - Computing climatology...
[2021-11-02 09:16:41] - Done.
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")
station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:16:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:44] Number of windows considered: 1...
[2021-11-02 09:16:44] Bias-correcting 1 members separately...
[2021-11-02 09:16:44] Done.
Validation 2, 20 remaining
[2021-11-02 09:16:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:45] Number of windows considered: 1...
[2021-11-02 09:16:45] Bias-correcting 1 members separately...
[2021-11-02 09:16:45] Done.
Validation 3, 19 remaining
[2021-11-02 09:16:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:46] Number of windows considered: 1...
[2021-11-02 09:16:46] Bias-correcting 1 members separately...
[2021-11-02 09:16:46] Done.
Validation 4, 18 remaining
[2021-11-02 09:16:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:46] Number of windows considered: 1...
[2021-11-02 09:16:46] Bias-correcting 1 members separately...
[2021-11-02 09:16:46] Done.
Validation 5, 17 remaining
[2021-11-02 09:16:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:47] Number of windows considered: 1...
[2021-11-02 09:16:47] Bias-correcting 1 members separately...
[2021-11-02 09:16:47] Done.
Validation 6, 16 remaining
[2021-11-02 09:16:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:47] Number of windows considered: 1...
[2021-11-02 09:16:47] Bias-correcting 1 members separately...
[2021-11-02 09:16:47] Done.
Validation 7, 15 remaining
[2021-11-02 09:16:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:48] Number of windows considered: 1...
[2021-11-02 09:16:48] Bias-correcting 1 members separately...
[2021-11-02 09:16:48] Done.
Validation 8, 14 remaining
[2021-11-02 09:16:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:49] Number of windows considered: 1...
[2021-11-02 09:16:49] Bias-correcting 1 members separately...
[2021-11-02 09:16:49] Done.
Validation 9, 13 remaining
[2021-11-02 09:16:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:49] Number of windows considered: 1...
[2021-11-02 09:16:49] Bias-correcting 1 members separately...
[2021-11-02 09:16:49] Done.
Validation 10, 12 remaining
[2021-11-02 09:16:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:50] Number of windows considered: 1...
[2021-11-02 09:16:50] Bias-correcting 1 members separately...
[2021-11-02 09:16:50] Done.
Validation 11, 11 remaining
[2021-11-02 09:16:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:51] Number of windows considered: 1...
[2021-11-02 09:16:51] Bias-correcting 1 members separately...
[2021-11-02 09:16:51] Done.
Validation 12, 10 remaining
[2021-11-02 09:16:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:51] Number of windows considered: 1...
[2021-11-02 09:16:51] Bias-correcting 1 members separately...
[2021-11-02 09:16:51] Done.
Validation 13, 9 remaining
[2021-11-02 09:16:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:52] Number of windows considered: 1...
[2021-11-02 09:16:52] Bias-correcting 1 members separately...
[2021-11-02 09:16:52] Done.
Validation 14, 8 remaining
[2021-11-02 09:16:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:53] Number of windows considered: 1...
[2021-11-02 09:16:53] Bias-correcting 1 members separately...
[2021-11-02 09:16:53] Done.
Validation 15, 7 remaining
[2021-11-02 09:16:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:53] Number of windows considered: 1...
[2021-11-02 09:16:53] Bias-correcting 1 members separately...
[2021-11-02 09:16:53] Done.
Validation 16, 6 remaining
[2021-11-02 09:16:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:54] Number of windows considered: 1...
[2021-11-02 09:16:54] Bias-correcting 1 members separately...
[2021-11-02 09:16:54] Done.
Validation 17, 5 remaining
[2021-11-02 09:16:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:55] Number of windows considered: 1...
[2021-11-02 09:16:55] Bias-correcting 1 members separately...
[2021-11-02 09:16:55] Done.
Validation 18, 4 remaining
[2021-11-02 09:16:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:55] Number of windows considered: 1...
[2021-11-02 09:16:55] Bias-correcting 1 members separately...
[2021-11-02 09:16:55] Done.
Validation 19, 3 remaining
[2021-11-02 09:16:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:56] Number of windows considered: 1...
[2021-11-02 09:16:56] Bias-correcting 1 members separately...
[2021-11-02 09:16:56] Done.
Validation 20, 2 remaining
[2021-11-02 09:16:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:57] Number of windows considered: 1...
[2021-11-02 09:16:57] Bias-correcting 1 members separately...
[2021-11-02 09:16:57] Done.
Validation 21, 1 remaining
[2021-11-02 09:16:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:58] Number of windows considered: 1...
[2021-11-02 09:16:58] Bias-correcting 1 members separately...
[2021-11-02 09:16:58] Done.
Validation 22, 0 remaining
[2021-11-02 09:16:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:16:58] Number of windows considered: 1...
[2021-11-02 09:16:58] Bias-correcting 1 members separately...
[2021-11-02 09:16:58] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-11-02 09:16:59] Performing annual aggregation...
[2021-11-02 09:16:59] Done.
[2021-11-02 09:16:59] - Computing climatology...
[2021-11-02 09:16:59] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.pqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:17:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:07] Number of windows considered: 1...
[2021-11-02 09:17:07] Bias-correcting 1 members separately...
[2021-11-02 09:17:07] Done.
Validation 2, 20 remaining
[2021-11-02 09:17:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:08] Number of windows considered: 1...
[2021-11-02 09:17:08] Bias-correcting 1 members separately...
[2021-11-02 09:17:08] Done.
Validation 3, 19 remaining
[2021-11-02 09:17:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:09] Number of windows considered: 1...
[2021-11-02 09:17:09] Bias-correcting 1 members separately...
[2021-11-02 09:17:09] Done.
Validation 4, 18 remaining
[2021-11-02 09:17:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:10] Number of windows considered: 1...
[2021-11-02 09:17:10] Bias-correcting 1 members separately...
[2021-11-02 09:17:10] Done.
Validation 5, 17 remaining
[2021-11-02 09:17:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:10] Number of windows considered: 1...
[2021-11-02 09:17:10] Bias-correcting 1 members separately...
[2021-11-02 09:17:10] Done.
Validation 6, 16 remaining
[2021-11-02 09:17:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:11] Number of windows considered: 1...
[2021-11-02 09:17:11] Bias-correcting 1 members separately...
[2021-11-02 09:17:11] Done.
Validation 7, 15 remaining
[2021-11-02 09:17:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:12] Number of windows considered: 1...
[2021-11-02 09:17:12] Bias-correcting 1 members separately...
[2021-11-02 09:17:12] Done.
Validation 8, 14 remaining
[2021-11-02 09:17:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:13] Number of windows considered: 1...
[2021-11-02 09:17:13] Bias-correcting 1 members separately...
[2021-11-02 09:17:13] Done.
Validation 9, 13 remaining
[2021-11-02 09:17:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:13] Number of windows considered: 1...
[2021-11-02 09:17:13] Bias-correcting 1 members separately...
[2021-11-02 09:17:14] Done.
Validation 10, 12 remaining
[2021-11-02 09:17:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:14] Number of windows considered: 1...
[2021-11-02 09:17:14] Bias-correcting 1 members separately...
[2021-11-02 09:17:14] Done.
Validation 11, 11 remaining
[2021-11-02 09:17:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:15] Number of windows considered: 1...
[2021-11-02 09:17:15] Bias-correcting 1 members separately...
[2021-11-02 09:17:15] Done.
Validation 12, 10 remaining
[2021-11-02 09:17:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:16] Number of windows considered: 1...
[2021-11-02 09:17:16] Bias-correcting 1 members separately...
[2021-11-02 09:17:16] Done.
Validation 13, 9 remaining
[2021-11-02 09:17:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:17] Number of windows considered: 1...
[2021-11-02 09:17:17] Bias-correcting 1 members separately...
[2021-11-02 09:17:17] Done.
Validation 14, 8 remaining
[2021-11-02 09:17:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:17] Number of windows considered: 1...
[2021-11-02 09:17:17] Bias-correcting 1 members separately...
[2021-11-02 09:17:17] Done.
Validation 15, 7 remaining
[2021-11-02 09:17:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:18] Number of windows considered: 1...
[2021-11-02 09:17:18] Bias-correcting 1 members separately...
[2021-11-02 09:17:18] Done.
Validation 16, 6 remaining
[2021-11-02 09:17:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:19] Number of windows considered: 1...
[2021-11-02 09:17:19] Bias-correcting 1 members separately...
[2021-11-02 09:17:19] Done.
Validation 17, 5 remaining
[2021-11-02 09:17:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:19] Number of windows considered: 1...
[2021-11-02 09:17:19] Bias-correcting 1 members separately...
[2021-11-02 09:17:19] Done.
Validation 18, 4 remaining
[2021-11-02 09:17:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:20] Number of windows considered: 1...
[2021-11-02 09:17:20] Bias-correcting 1 members separately...
[2021-11-02 09:17:20] Done.
Validation 19, 3 remaining
[2021-11-02 09:17:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:21] Number of windows considered: 1...
[2021-11-02 09:17:21] Bias-correcting 1 members separately...
[2021-11-02 09:17:21] Done.
Validation 20, 2 remaining
[2021-11-02 09:17:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:21] Number of windows considered: 1...
[2021-11-02 09:17:21] Bias-correcting 1 members separately...
[2021-11-02 09:17:21] Done.
Validation 21, 1 remaining
[2021-11-02 09:17:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:22] Number of windows considered: 1...
[2021-11-02 09:17:22] Bias-correcting 1 members separately...
[2021-11-02 09:17:22] Done.
Validation 22, 0 remaining
[2021-11-02 09:17:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:23] Number of windows considered: 1...
[2021-11-02 09:17:23] Bias-correcting 1 members separately...
[2021-11-02 09:17:23] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-11-02 09:17:23] Performing annual aggregation...
[2021-11-02 09:17:23] Done.
[2021-11-02 09:17:23] - Computing climatology...
[2021-11-02 09:17:23] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.eqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:17:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:34] Number of windows considered: 1...
[2021-11-02 09:17:34] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:34] Done.
Validation 2, 20 remaining
[2021-11-02 09:17:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:34] Number of windows considered: 1...
[2021-11-02 09:17:34] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:35] Done.
Validation 3, 19 remaining
[2021-11-02 09:17:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:35] Number of windows considered: 1...
[2021-11-02 09:17:35] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:35] Done.
Validation 4, 18 remaining
[2021-11-02 09:17:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:36] Number of windows considered: 1...
[2021-11-02 09:17:36] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:36] Done.
Validation 5, 17 remaining
[2021-11-02 09:17:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:37] Number of windows considered: 1...
[2021-11-02 09:17:37] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:37] Done.
Validation 6, 16 remaining
[2021-11-02 09:17:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:37] Number of windows considered: 1...
[2021-11-02 09:17:37] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:17:38] Done.
Validation 7, 15 remaining
[2021-11-02 09:17:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:38] Number of windows considered: 1...
[2021-11-02 09:17:38] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:38] Done.
Validation 8, 14 remaining
[2021-11-02 09:17:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:39] Number of windows considered: 1...
[2021-11-02 09:17:39] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:39] Done.
Validation 9, 13 remaining
[2021-11-02 09:17:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:40] Number of windows considered: 1...
[2021-11-02 09:17:40] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:40] Done.
Validation 10, 12 remaining
[2021-11-02 09:17:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:41] Number of windows considered: 1...
[2021-11-02 09:17:41] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:41] Done.
Validation 11, 11 remaining
[2021-11-02 09:17:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:41] Number of windows considered: 1...
[2021-11-02 09:17:41] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:41] Done.
Validation 12, 10 remaining
[2021-11-02 09:17:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:42] Number of windows considered: 1...
[2021-11-02 09:17:42] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:42] Done.
Validation 13, 9 remaining
[2021-11-02 09:17:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:43] Number of windows considered: 1...
[2021-11-02 09:17:43] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:43] Done.
Validation 14, 8 remaining
[2021-11-02 09:17:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:44] Number of windows considered: 1...
[2021-11-02 09:17:44] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:44] Done.
Validation 15, 7 remaining
[2021-11-02 09:17:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:44] Number of windows considered: 1...
[2021-11-02 09:17:44] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:45] Done.
Validation 16, 6 remaining
[2021-11-02 09:17:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:45] Number of windows considered: 1...
[2021-11-02 09:17:45] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:45] Done.
Validation 17, 5 remaining
[2021-11-02 09:17:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:46] Number of windows considered: 1...
[2021-11-02 09:17:46] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:46] Done.
Validation 18, 4 remaining
[2021-11-02 09:17:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:47] Number of windows considered: 1...
[2021-11-02 09:17:47] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:47] Done.
Validation 19, 3 remaining
[2021-11-02 09:17:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:48] Number of windows considered: 1...
[2021-11-02 09:17:48] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:48] Done.
Validation 20, 2 remaining
[2021-11-02 09:17:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:49] Number of windows considered: 1...
[2021-11-02 09:17:49] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:49] Done.
Validation 21, 1 remaining
[2021-11-02 09:17:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:49] Number of windows considered: 1...
[2021-11-02 09:17:49] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:49] Done.
Validation 22, 0 remaining
[2021-11-02 09:17:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:50] Number of windows considered: 1...
[2021-11-02 09:17:50] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:50] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-11-02 09:17:51] Performing annual aggregation...
[2021-11-02 09:17:51] Done.
[2021-11-02 09:17:51] - Computing climatology...
[2021-11-02 09:17:51] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:17:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:17:59] Number of windows considered: 1...
[2021-11-02 09:17:59] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:17:59] Done.
Validation 2, 20 remaining
[2021-11-02 09:18:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:00] Number of windows considered: 1...
[2021-11-02 09:18:00] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:18:00] Done.
Validation 3, 19 remaining
[2021-11-02 09:18:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:01] Number of windows considered: 1...
[2021-11-02 09:18:01] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:18:01] Done.
Validation 4, 18 remaining
[2021-11-02 09:18:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:01] Number of windows considered: 1...
[2021-11-02 09:18:01] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:18:01] Done.
Validation 5, 17 remaining
[2021-11-02 09:18:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:02] Number of windows considered: 1...
[2021-11-02 09:18:02] Bias-correcting 1 members separately...
[2021-11-02 09:18:02] Done.
Validation 6, 16 remaining
[2021-11-02 09:18:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:03] Number of windows considered: 1...
[2021-11-02 09:18:03] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 09:18:03] Done.
Validation 7, 15 remaining
[2021-11-02 09:18:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:04] Number of windows considered: 1...
[2021-11-02 09:18:04] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:18:04] Done.
Validation 8, 14 remaining
[2021-11-02 09:18:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:04] Number of windows considered: 1...
[2021-11-02 09:18:04] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:18:05] Done.
Validation 9, 13 remaining
[2021-11-02 09:18:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:05] Number of windows considered: 1...
[2021-11-02 09:18:05] Bias-correcting 1 members separately...
[2021-11-02 09:18:05] Done.
Validation 10, 12 remaining
[2021-11-02 09:18:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:06] Number of windows considered: 1...
[2021-11-02 09:18:06] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:18:06] Done.
Validation 11, 11 remaining
[2021-11-02 09:18:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:07] Number of windows considered: 1...
[2021-11-02 09:18:07] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:18:07] Done.
Validation 12, 10 remaining
[2021-11-02 09:18:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:07] Number of windows considered: 1...
[2021-11-02 09:18:07] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:18:07] Done.
Validation 13, 9 remaining
[2021-11-02 09:18:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:08] Number of windows considered: 1...
[2021-11-02 09:18:08] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:18:08] Done.
Validation 14, 8 remaining
[2021-11-02 09:18:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:09] Number of windows considered: 1...
[2021-11-02 09:18:09] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:18:09] Done.
Validation 15, 7 remaining
[2021-11-02 09:18:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:09] Number of windows considered: 1...
[2021-11-02 09:18:09] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:18:09] Done.
Validation 16, 6 remaining
[2021-11-02 09:18:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:10] Number of windows considered: 1...
[2021-11-02 09:18:10] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:18:10] Done.
Validation 17, 5 remaining
[2021-11-02 09:18:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:11] Number of windows considered: 1...
[2021-11-02 09:18:11] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 09:18:11] Done.
Validation 18, 4 remaining
[2021-11-02 09:18:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:11] Number of windows considered: 1...
[2021-11-02 09:18:11] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:18:11] Done.
Validation 19, 3 remaining
[2021-11-02 09:18:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:12] Number of windows considered: 1...
[2021-11-02 09:18:12] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 09:18:12] Done.
Validation 20, 2 remaining
[2021-11-02 09:18:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:13] Number of windows considered: 1...
[2021-11-02 09:18:13] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:18:13] Done.
Validation 21, 1 remaining
[2021-11-02 09:18:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:13] Number of windows considered: 1...
[2021-11-02 09:18:13] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:18:13] Done.
Validation 22, 0 remaining
[2021-11-02 09:18:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:14] Number of windows considered: 1...
[2021-11-02 09:18:14] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:18:14] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-11-02 09:18:15] Performing annual aggregation...
[2021-11-02 09:18:15] Done.
[2021-11-02 09:18:15] - Computing climatology...
[2021-11-02 09:18:15] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm2.cl2 <- index.cal.station.cl2
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores
PQM-WT2 EQM-WT2 GPQM2-WT2 GPQM-WT2
0.6430372 0.6373537 0.6222438 0.2806547
scores.st1.wt2 <- scores
WT3
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))
station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
[2021-11-02 09:18:40] Performing annual aggregation...
[2021-11-02 09:18:40] Done.
[2021-11-02 09:18:40] - Computing climatology...
[2021-11-02 09:18:40] - Done.
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)
index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
[2021-11-02 09:18:40] Performing annual aggregation...
[2021-11-02 09:18:40] Done.
[2021-11-02 09:18:40] - Computing climatology...
[2021-11-02 09:18:40] - Done.
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")
station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:18:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:45] Number of windows considered: 1...
[2021-11-02 09:18:45] Bias-correcting 1 members separately...
[2021-11-02 09:18:45] Done.
Validation 2, 20 remaining
[2021-11-02 09:18:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:45] Number of windows considered: 1...
[2021-11-02 09:18:45] Bias-correcting 1 members separately...
[2021-11-02 09:18:45] Done.
Validation 3, 19 remaining
[2021-11-02 09:18:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:46] Number of windows considered: 1...
[2021-11-02 09:18:46] Bias-correcting 1 members separately...
[2021-11-02 09:18:46] Done.
Validation 4, 18 remaining
[2021-11-02 09:18:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:47] Number of windows considered: 1...
[2021-11-02 09:18:47] Bias-correcting 1 members separately...
[2021-11-02 09:18:47] Done.
Validation 5, 17 remaining
[2021-11-02 09:18:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:48] Number of windows considered: 1...
[2021-11-02 09:18:48] Bias-correcting 1 members separately...
[2021-11-02 09:18:48] Done.
Validation 6, 16 remaining
[2021-11-02 09:18:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:48] Number of windows considered: 1...
[2021-11-02 09:18:48] Bias-correcting 1 members separately...
[2021-11-02 09:18:49] Done.
Validation 7, 15 remaining
[2021-11-02 09:18:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:49] Number of windows considered: 1...
[2021-11-02 09:18:49] Bias-correcting 1 members separately...
[2021-11-02 09:18:49] Done.
Validation 8, 14 remaining
[2021-11-02 09:18:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:50] Number of windows considered: 1...
[2021-11-02 09:18:50] Bias-correcting 1 members separately...
[2021-11-02 09:18:50] Done.
Validation 9, 13 remaining
[2021-11-02 09:18:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:51] Number of windows considered: 1...
[2021-11-02 09:18:51] Bias-correcting 1 members separately...
[2021-11-02 09:18:51] Done.
Validation 10, 12 remaining
[2021-11-02 09:18:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:52] Number of windows considered: 1...
[2021-11-02 09:18:52] Bias-correcting 1 members separately...
[2021-11-02 09:18:52] Done.
Validation 11, 11 remaining
[2021-11-02 09:18:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:52] Number of windows considered: 1...
[2021-11-02 09:18:52] Bias-correcting 1 members separately...
[2021-11-02 09:18:52] Done.
Validation 12, 10 remaining
[2021-11-02 09:18:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:53] Number of windows considered: 1...
[2021-11-02 09:18:53] Bias-correcting 1 members separately...
[2021-11-02 09:18:53] Done.
Validation 13, 9 remaining
[2021-11-02 09:18:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:54] Number of windows considered: 1...
[2021-11-02 09:18:54] Bias-correcting 1 members separately...
[2021-11-02 09:18:54] Done.
Validation 14, 8 remaining
[2021-11-02 09:18:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:55] Number of windows considered: 1...
[2021-11-02 09:18:55] Bias-correcting 1 members separately...
[2021-11-02 09:18:55] Done.
Validation 15, 7 remaining
[2021-11-02 09:18:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:56] Number of windows considered: 1...
[2021-11-02 09:18:56] Bias-correcting 1 members separately...
[2021-11-02 09:18:56] Done.
Validation 16, 6 remaining
[2021-11-02 09:18:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:56] Number of windows considered: 1...
[2021-11-02 09:18:56] Bias-correcting 1 members separately...
[2021-11-02 09:18:56] Done.
Validation 17, 5 remaining
[2021-11-02 09:18:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:57] Number of windows considered: 1...
[2021-11-02 09:18:57] Bias-correcting 1 members separately...
[2021-11-02 09:18:57] Done.
Validation 18, 4 remaining
[2021-11-02 09:18:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:58] Number of windows considered: 1...
[2021-11-02 09:18:58] Bias-correcting 1 members separately...
[2021-11-02 09:18:58] Done.
Validation 19, 3 remaining
[2021-11-02 09:18:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:59] Number of windows considered: 1...
[2021-11-02 09:18:59] Bias-correcting 1 members separately...
[2021-11-02 09:18:59] Done.
Validation 20, 2 remaining
[2021-11-02 09:18:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:18:59] Number of windows considered: 1...
[2021-11-02 09:18:59] Bias-correcting 1 members separately...
[2021-11-02 09:19:00] Done.
Validation 21, 1 remaining
[2021-11-02 09:19:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:00] Number of windows considered: 1...
[2021-11-02 09:19:00] Bias-correcting 1 members separately...
[2021-11-02 09:19:00] Done.
Validation 22, 0 remaining
[2021-11-02 09:19:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:01] Number of windows considered: 1...
[2021-11-02 09:19:01] Bias-correcting 1 members separately...
[2021-11-02 09:19:01] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-11-02 09:19:02] Performing annual aggregation...
[2021-11-02 09:19:02] Done.
[2021-11-02 09:19:02] - Computing climatology...
[2021-11-02 09:19:02] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.pqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:19:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:10] Number of windows considered: 1...
[2021-11-02 09:19:10] Bias-correcting 1 members separately...
[2021-11-02 09:19:10] Done.
Validation 2, 20 remaining
[2021-11-02 09:19:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:11] Number of windows considered: 1...
[2021-11-02 09:19:11] Bias-correcting 1 members separately...
[2021-11-02 09:19:11] Done.
Validation 3, 19 remaining
[2021-11-02 09:19:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:12] Number of windows considered: 1...
[2021-11-02 09:19:12] Bias-correcting 1 members separately...
[2021-11-02 09:19:12] Done.
Validation 4, 18 remaining
[2021-11-02 09:19:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:13] Number of windows considered: 1...
[2021-11-02 09:19:13] Bias-correcting 1 members separately...
[2021-11-02 09:19:13] Done.
Validation 5, 17 remaining
[2021-11-02 09:19:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:14] Number of windows considered: 1...
[2021-11-02 09:19:14] Bias-correcting 1 members separately...
[2021-11-02 09:19:14] Done.
Validation 6, 16 remaining
[2021-11-02 09:19:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:15] Number of windows considered: 1...
[2021-11-02 09:19:15] Bias-correcting 1 members separately...
[2021-11-02 09:19:15] Done.
Validation 7, 15 remaining
[2021-11-02 09:19:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:15] Number of windows considered: 1...
[2021-11-02 09:19:15] Bias-correcting 1 members separately...
[2021-11-02 09:19:15] Done.
Validation 8, 14 remaining
[2021-11-02 09:19:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:16] Number of windows considered: 1...
[2021-11-02 09:19:16] Bias-correcting 1 members separately...
[2021-11-02 09:19:16] Done.
Validation 9, 13 remaining
[2021-11-02 09:19:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:17] Number of windows considered: 1...
[2021-11-02 09:19:17] Bias-correcting 1 members separately...
[2021-11-02 09:19:17] Done.
Validation 10, 12 remaining
[2021-11-02 09:19:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:18] Number of windows considered: 1...
[2021-11-02 09:19:18] Bias-correcting 1 members separately...
[2021-11-02 09:19:18] Done.
Validation 11, 11 remaining
[2021-11-02 09:19:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:19] Number of windows considered: 1...
[2021-11-02 09:19:19] Bias-correcting 1 members separately...
[2021-11-02 09:19:19] Done.
Validation 12, 10 remaining
[2021-11-02 09:19:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:19] Number of windows considered: 1...
[2021-11-02 09:19:19] Bias-correcting 1 members separately...
[2021-11-02 09:19:19] Done.
Validation 13, 9 remaining
[2021-11-02 09:19:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:20] Number of windows considered: 1...
[2021-11-02 09:19:20] Bias-correcting 1 members separately...
[2021-11-02 09:19:20] Done.
Validation 14, 8 remaining
[2021-11-02 09:19:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:21] Number of windows considered: 1...
[2021-11-02 09:19:21] Bias-correcting 1 members separately...
[2021-11-02 09:19:21] Done.
Validation 15, 7 remaining
[2021-11-02 09:19:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:21] Number of windows considered: 1...
[2021-11-02 09:19:21] Bias-correcting 1 members separately...
[2021-11-02 09:19:21] Done.
Validation 16, 6 remaining
[2021-11-02 09:19:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:22] Number of windows considered: 1...
[2021-11-02 09:19:22] Bias-correcting 1 members separately...
[2021-11-02 09:19:22] Done.
Validation 17, 5 remaining
[2021-11-02 09:19:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:23] Number of windows considered: 1...
[2021-11-02 09:19:23] Bias-correcting 1 members separately...
[2021-11-02 09:19:23] Done.
Validation 18, 4 remaining
[2021-11-02 09:19:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:23] Number of windows considered: 1...
[2021-11-02 09:19:23] Bias-correcting 1 members separately...
[2021-11-02 09:19:24] Done.
Validation 19, 3 remaining
[2021-11-02 09:19:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:24] Number of windows considered: 1...
[2021-11-02 09:19:24] Bias-correcting 1 members separately...
[2021-11-02 09:19:24] Done.
Validation 20, 2 remaining
[2021-11-02 09:19:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:25] Number of windows considered: 1...
[2021-11-02 09:19:25] Bias-correcting 1 members separately...
[2021-11-02 09:19:25] Done.
Validation 21, 1 remaining
[2021-11-02 09:19:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:26] Number of windows considered: 1...
[2021-11-02 09:19:26] Bias-correcting 1 members separately...
[2021-11-02 09:19:26] Done.
Validation 22, 0 remaining
[2021-11-02 09:19:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:26] Number of windows considered: 1...
[2021-11-02 09:19:26] Bias-correcting 1 members separately...
[2021-11-02 09:19:27] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-11-02 09:19:27] Performing annual aggregation...
[2021-11-02 09:19:27] Done.
[2021-11-02 09:19:27] - Computing climatology...
[2021-11-02 09:19:27] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.eqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:19:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:38] Number of windows considered: 1...
[2021-11-02 09:19:38] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:38] Done.
Validation 2, 20 remaining
[2021-11-02 09:19:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:39] Number of windows considered: 1...
[2021-11-02 09:19:39] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:39] Done.
Validation 3, 19 remaining
[2021-11-02 09:19:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:40] Number of windows considered: 1...
[2021-11-02 09:19:40] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:19:40] Done.
Validation 4, 18 remaining
[2021-11-02 09:19:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:40] Number of windows considered: 1...
[2021-11-02 09:19:40] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:40] Done.
Validation 5, 17 remaining
[2021-11-02 09:19:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:41] Number of windows considered: 1...
[2021-11-02 09:19:41] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:41] Done.
Validation 6, 16 remaining
[2021-11-02 09:19:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:42] Number of windows considered: 1...
[2021-11-02 09:19:42] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:42] Done.
Validation 7, 15 remaining
[2021-11-02 09:19:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:43] Number of windows considered: 1...
[2021-11-02 09:19:43] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:19:43] Done.
Validation 8, 14 remaining
[2021-11-02 09:19:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:43] Number of windows considered: 1...
[2021-11-02 09:19:43] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:43] Done.
Validation 9, 13 remaining
[2021-11-02 09:19:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:44] Number of windows considered: 1...
[2021-11-02 09:19:44] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:44] Done.
Validation 10, 12 remaining
[2021-11-02 09:19:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:45] Number of windows considered: 1...
[2021-11-02 09:19:45] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:19:45] Done.
Validation 11, 11 remaining
[2021-11-02 09:19:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:46] Number of windows considered: 1...
[2021-11-02 09:19:46] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:46] Done.
Validation 12, 10 remaining
[2021-11-02 09:19:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:47] Number of windows considered: 1...
[2021-11-02 09:19:47] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:47] Done.
Validation 13, 9 remaining
[2021-11-02 09:19:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:47] Number of windows considered: 1...
[2021-11-02 09:19:47] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:47] Done.
Validation 14, 8 remaining
[2021-11-02 09:19:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:48] Number of windows considered: 1...
[2021-11-02 09:19:48] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:48] Done.
Validation 15, 7 remaining
[2021-11-02 09:19:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:49] Number of windows considered: 1...
[2021-11-02 09:19:49] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:49] Done.
Validation 16, 6 remaining
[2021-11-02 09:19:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:50] Number of windows considered: 1...
[2021-11-02 09:19:50] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:50] Done.
Validation 17, 5 remaining
[2021-11-02 09:19:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:50] Number of windows considered: 1...
[2021-11-02 09:19:50] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:51] Done.
Validation 18, 4 remaining
[2021-11-02 09:19:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:51] Number of windows considered: 1...
[2021-11-02 09:19:51] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:51] Done.
Validation 19, 3 remaining
[2021-11-02 09:19:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:52] Number of windows considered: 1...
[2021-11-02 09:19:52] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:52] Done.
Validation 20, 2 remaining
[2021-11-02 09:19:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:53] Number of windows considered: 1...
[2021-11-02 09:19:53] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:19:53] Done.
Validation 21, 1 remaining
[2021-11-02 09:19:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:54] Number of windows considered: 1...
[2021-11-02 09:19:54] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:19:54] Done.
Validation 22, 0 remaining
[2021-11-02 09:19:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:19:55] Number of windows considered: 1...
[2021-11-02 09:19:55] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:19:55] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-11-02 09:19:55] Performing annual aggregation...
[2021-11-02 09:19:55] Done.
[2021-11-02 09:19:55] - Computing climatology...
[2021-11-02 09:19:55] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:20:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:07] Number of windows considered: 1...
[2021-11-02 09:20:07] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:07] Done.
Validation 2, 20 remaining
[2021-11-02 09:20:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:07] Number of windows considered: 1...
[2021-11-02 09:20:07] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:07] Done.
Validation 3, 19 remaining
[2021-11-02 09:20:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:08] Number of windows considered: 1...
[2021-11-02 09:20:08] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:08] Done.
Validation 4, 18 remaining
[2021-11-02 09:20:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:09] Number of windows considered: 1...
[2021-11-02 09:20:09] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:09] Done.
Validation 5, 17 remaining
[2021-11-02 09:20:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:09] Number of windows considered: 1...
[2021-11-02 09:20:09] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:09] Done.
Validation 6, 16 remaining
[2021-11-02 09:20:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:10] Number of windows considered: 1...
[2021-11-02 09:20:10] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:10] Done.
Validation 7, 15 remaining
[2021-11-02 09:20:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:10] Number of windows considered: 1...
[2021-11-02 09:20:10] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:11] Done.
Validation 8, 14 remaining
[2021-11-02 09:20:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:11] Number of windows considered: 1...
[2021-11-02 09:20:11] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:11] Done.
Validation 9, 13 remaining
[2021-11-02 09:20:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:12] Number of windows considered: 1...
[2021-11-02 09:20:12] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:12] Done.
Validation 10, 12 remaining
[2021-11-02 09:20:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:13] Number of windows considered: 1...
[2021-11-02 09:20:13] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:13] Done.
Validation 11, 11 remaining
[2021-11-02 09:20:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:13] Number of windows considered: 1...
[2021-11-02 09:20:13] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:13] Done.
Validation 12, 10 remaining
[2021-11-02 09:20:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:14] Number of windows considered: 1...
[2021-11-02 09:20:14] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:14] Done.
Validation 13, 9 remaining
[2021-11-02 09:20:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:15] Number of windows considered: 1...
[2021-11-02 09:20:15] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:15] Done.
Validation 14, 8 remaining
[2021-11-02 09:20:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:15] Number of windows considered: 1...
[2021-11-02 09:20:15] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:16] Done.
Validation 15, 7 remaining
[2021-11-02 09:20:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:16] Number of windows considered: 1...
[2021-11-02 09:20:16] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:16] Done.
Validation 16, 6 remaining
[2021-11-02 09:20:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:17] Number of windows considered: 1...
[2021-11-02 09:20:17] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:17] Done.
Validation 17, 5 remaining
[2021-11-02 09:20:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:18] Number of windows considered: 1...
[2021-11-02 09:20:18] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:18] Done.
Validation 18, 4 remaining
[2021-11-02 09:20:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:18] Number of windows considered: 1...
[2021-11-02 09:20:18] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:19] Done.
Validation 19, 3 remaining
[2021-11-02 09:20:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:19] Number of windows considered: 1...
[2021-11-02 09:20:19] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:19] Done.
Validation 20, 2 remaining
[2021-11-02 09:20:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:20] Number of windows considered: 1...
[2021-11-02 09:20:20] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:20] Done.
Validation 21, 1 remaining
[2021-11-02 09:20:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:21] Number of windows considered: 1...
[2021-11-02 09:20:21] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:21] Done.
Validation 22, 0 remaining
[2021-11-02 09:20:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:22] Number of windows considered: 1...
[2021-11-02 09:20:22] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-11-02 09:20:22] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-11-02 09:20:22] Performing annual aggregation...
[2021-11-02 09:20:22] Done.
[2021-11-02 09:20:22] - Computing climatology...
[2021-11-02 09:20:22] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm2.cl3 <- index.cal.station.cl3
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
PQM-WT3 EQM-WT3 GPQM2-WT3 GPQM-WT3
0.78840261 0.77251393 0.52976656 0.03963651
scores.st1.wt3 <- scores
WT4
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))
station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
[2021-11-02 09:20:44] Performing annual aggregation...
[2021-11-02 09:20:44] Done.
[2021-11-02 09:20:44] - Computing climatology...
[2021-11-02 09:20:44] - Done.
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)
index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
[2021-11-02 09:20:45] Performing annual aggregation...
[2021-11-02 09:20:45] Done.
[2021-11-02 09:20:45] - Computing climatology...
[2021-11-02 09:20:45] - Done.
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")
station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:20:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:49] Number of windows considered: 1...
[2021-11-02 09:20:49] Bias-correcting 1 members separately...
[2021-11-02 09:20:49] Done.
Validation 2, 20 remaining
[2021-11-02 09:20:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:50] Number of windows considered: 1...
[2021-11-02 09:20:50] Bias-correcting 1 members separately...
[2021-11-02 09:20:50] Done.
Validation 3, 19 remaining
[2021-11-02 09:20:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:50] Number of windows considered: 1...
[2021-11-02 09:20:50] Bias-correcting 1 members separately...
[2021-11-02 09:20:50] Done.
Validation 4, 18 remaining
[2021-11-02 09:20:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:51] Number of windows considered: 1...
[2021-11-02 09:20:51] Bias-correcting 1 members separately...
[2021-11-02 09:20:51] Done.
Validation 5, 17 remaining
[2021-11-02 09:20:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:52] Number of windows considered: 1...
[2021-11-02 09:20:52] Bias-correcting 1 members separately...
[2021-11-02 09:20:52] Done.
Validation 6, 16 remaining
[2021-11-02 09:20:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:52] Number of windows considered: 1...
[2021-11-02 09:20:52] Bias-correcting 1 members separately...
[2021-11-02 09:20:52] Done.
Validation 7, 15 remaining
[2021-11-02 09:20:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:53] Number of windows considered: 1...
[2021-11-02 09:20:53] Bias-correcting 1 members separately...
[2021-11-02 09:20:53] Done.
Validation 8, 14 remaining
[2021-11-02 09:20:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:54] Number of windows considered: 1...
[2021-11-02 09:20:54] Bias-correcting 1 members separately...
[2021-11-02 09:20:54] Done.
Validation 9, 13 remaining
[2021-11-02 09:20:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:55] Number of windows considered: 1...
[2021-11-02 09:20:55] Bias-correcting 1 members separately...
[2021-11-02 09:20:55] Done.
Validation 10, 12 remaining
[2021-11-02 09:20:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:55] Number of windows considered: 1...
[2021-11-02 09:20:55] Bias-correcting 1 members separately...
[2021-11-02 09:20:55] Done.
Validation 11, 11 remaining
[2021-11-02 09:20:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:56] Number of windows considered: 1...
[2021-11-02 09:20:56] Bias-correcting 1 members separately...
[2021-11-02 09:20:56] Done.
Validation 12, 10 remaining
[2021-11-02 09:20:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:57] Number of windows considered: 1...
[2021-11-02 09:20:57] Bias-correcting 1 members separately...
[2021-11-02 09:20:57] Done.
Validation 13, 9 remaining
[2021-11-02 09:20:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:58] Number of windows considered: 1...
[2021-11-02 09:20:58] Bias-correcting 1 members separately...
[2021-11-02 09:20:58] Done.
Validation 14, 8 remaining
[2021-11-02 09:20:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:58] Number of windows considered: 1...
[2021-11-02 09:20:58] Bias-correcting 1 members separately...
[2021-11-02 09:20:58] Done.
Validation 15, 7 remaining
[2021-11-02 09:20:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:20:59] Number of windows considered: 1...
[2021-11-02 09:20:59] Bias-correcting 1 members separately...
[2021-11-02 09:20:59] Done.
Validation 16, 6 remaining
[2021-11-02 09:21:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:00] Number of windows considered: 1...
[2021-11-02 09:21:00] Bias-correcting 1 members separately...
[2021-11-02 09:21:00] Done.
Validation 17, 5 remaining
[2021-11-02 09:21:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:00] Number of windows considered: 1...
[2021-11-02 09:21:00] Bias-correcting 1 members separately...
[2021-11-02 09:21:00] Done.
Validation 18, 4 remaining
[2021-11-02 09:21:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:01] Number of windows considered: 1...
[2021-11-02 09:21:01] Bias-correcting 1 members separately...
[2021-11-02 09:21:01] Done.
Validation 19, 3 remaining
[2021-11-02 09:21:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:02] Number of windows considered: 1...
[2021-11-02 09:21:02] Bias-correcting 1 members separately...
[2021-11-02 09:21:02] Done.
Validation 20, 2 remaining
[2021-11-02 09:21:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:03] Number of windows considered: 1...
[2021-11-02 09:21:03] Bias-correcting 1 members separately...
[2021-11-02 09:21:03] Done.
Validation 21, 1 remaining
[2021-11-02 09:21:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:03] Number of windows considered: 1...
[2021-11-02 09:21:03] Bias-correcting 1 members separately...
[2021-11-02 09:21:03] Done.
Validation 22, 0 remaining
[2021-11-02 09:21:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:04] Number of windows considered: 1...
[2021-11-02 09:21:04] Bias-correcting 1 members separately...
[2021-11-02 09:21:04] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-11-02 09:21:05] Performing annual aggregation...
[2021-11-02 09:21:05] Done.
[2021-11-02 09:21:05] - Computing climatology...
[2021-11-02 09:21:05] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.pqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:21:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:15] Number of windows considered: 1...
[2021-11-02 09:21:15] Bias-correcting 1 members separately...
[2021-11-02 09:21:15] Done.
Validation 2, 20 remaining
[2021-11-02 09:21:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:16] Number of windows considered: 1...
[2021-11-02 09:21:16] Bias-correcting 1 members separately...
[2021-11-02 09:21:16] Done.
Validation 3, 19 remaining
[2021-11-02 09:21:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:16] Number of windows considered: 1...
[2021-11-02 09:21:16] Bias-correcting 1 members separately...
[2021-11-02 09:21:17] Done.
Validation 4, 18 remaining
[2021-11-02 09:21:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:17] Number of windows considered: 1...
[2021-11-02 09:21:17] Bias-correcting 1 members separately...
[2021-11-02 09:21:17] Done.
Validation 5, 17 remaining
[2021-11-02 09:21:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:18] Number of windows considered: 1...
[2021-11-02 09:21:18] Bias-correcting 1 members separately...
[2021-11-02 09:21:18] Done.
Validation 6, 16 remaining
[2021-11-02 09:21:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:19] Number of windows considered: 1...
[2021-11-02 09:21:19] Bias-correcting 1 members separately...
[2021-11-02 09:21:19] Done.
Validation 7, 15 remaining
[2021-11-02 09:21:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:20] Number of windows considered: 1...
[2021-11-02 09:21:20] Bias-correcting 1 members separately...
[2021-11-02 09:21:20] Done.
Validation 8, 14 remaining
[2021-11-02 09:21:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:21] Number of windows considered: 1...
[2021-11-02 09:21:21] Bias-correcting 1 members separately...
[2021-11-02 09:21:21] Done.
Validation 9, 13 remaining
[2021-11-02 09:21:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:21] Number of windows considered: 1...
[2021-11-02 09:21:21] Bias-correcting 1 members separately...
[2021-11-02 09:21:22] Done.
Validation 10, 12 remaining
[2021-11-02 09:21:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:22] Number of windows considered: 1...
[2021-11-02 09:21:22] Bias-correcting 1 members separately...
[2021-11-02 09:21:22] Done.
Validation 11, 11 remaining
[2021-11-02 09:21:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:23] Number of windows considered: 1...
[2021-11-02 09:21:23] Bias-correcting 1 members separately...
[2021-11-02 09:21:23] Done.
Validation 12, 10 remaining
[2021-11-02 09:21:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:23] Number of windows considered: 1...
[2021-11-02 09:21:23] Bias-correcting 1 members separately...
[2021-11-02 09:21:24] Done.
Validation 13, 9 remaining
[2021-11-02 09:21:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:24] Number of windows considered: 1...
[2021-11-02 09:21:24] Bias-correcting 1 members separately...
[2021-11-02 09:21:24] Done.
Validation 14, 8 remaining
[2021-11-02 09:21:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:25] Number of windows considered: 1...
[2021-11-02 09:21:25] Bias-correcting 1 members separately...
[2021-11-02 09:21:25] Done.
Validation 15, 7 remaining
[2021-11-02 09:21:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:26] Number of windows considered: 1...
[2021-11-02 09:21:26] Bias-correcting 1 members separately...
[2021-11-02 09:21:26] Done.
Validation 16, 6 remaining
[2021-11-02 09:21:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:26] Number of windows considered: 1...
[2021-11-02 09:21:26] Bias-correcting 1 members separately...
[2021-11-02 09:21:26] Done.
Validation 17, 5 remaining
[2021-11-02 09:21:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:27] Number of windows considered: 1...
[2021-11-02 09:21:27] Bias-correcting 1 members separately...
[2021-11-02 09:21:27] Done.
Validation 18, 4 remaining
[2021-11-02 09:21:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:28] Number of windows considered: 1...
[2021-11-02 09:21:28] Bias-correcting 1 members separately...
[2021-11-02 09:21:28] Done.
Validation 19, 3 remaining
[2021-11-02 09:21:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:29] Number of windows considered: 1...
[2021-11-02 09:21:29] Bias-correcting 1 members separately...
[2021-11-02 09:21:29] Done.
Validation 20, 2 remaining
[2021-11-02 09:21:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:29] Number of windows considered: 1...
[2021-11-02 09:21:29] Bias-correcting 1 members separately...
[2021-11-02 09:21:29] Done.
Validation 21, 1 remaining
[2021-11-02 09:21:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:30] Number of windows considered: 1...
[2021-11-02 09:21:30] Bias-correcting 1 members separately...
[2021-11-02 09:21:30] Done.
Validation 22, 0 remaining
[2021-11-02 09:21:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:31] Number of windows considered: 1...
[2021-11-02 09:21:31] Bias-correcting 1 members separately...
[2021-11-02 09:21:31] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-11-02 09:21:31] Performing annual aggregation...
[2021-11-02 09:21:31] Done.
[2021-11-02 09:21:31] - Computing climatology...
[2021-11-02 09:21:31] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.eqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:21:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:39] Number of windows considered: 1...
[2021-11-02 09:21:39] Bias-correcting 1 members separately...
[2021-11-02 09:21:39] Done.
Validation 2, 20 remaining
[2021-11-02 09:21:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:40] Number of windows considered: 1...
[2021-11-02 09:21:40] Bias-correcting 1 members separately...
[2021-11-02 09:21:40] Done.
Validation 3, 19 remaining
[2021-11-02 09:21:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:41] Number of windows considered: 1...
[2021-11-02 09:21:41] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:21:41] Done.
Validation 4, 18 remaining
[2021-11-02 09:21:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:42] Number of windows considered: 1...
[2021-11-02 09:21:42] Bias-correcting 1 members separately...
[2021-11-02 09:21:42] Done.
Validation 5, 17 remaining
[2021-11-02 09:21:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:42] Number of windows considered: 1...
[2021-11-02 09:21:42] Bias-correcting 1 members separately...
[2021-11-02 09:21:42] Done.
Validation 6, 16 remaining
[2021-11-02 09:21:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:43] Number of windows considered: 1...
[2021-11-02 09:21:43] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:21:43] Done.
Validation 7, 15 remaining
[2021-11-02 09:21:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:44] Number of windows considered: 1...
[2021-11-02 09:21:44] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:21:44] Done.
Validation 8, 14 remaining
[2021-11-02 09:21:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:45] Number of windows considered: 1...
[2021-11-02 09:21:45] Bias-correcting 1 members separately...
[2021-11-02 09:21:45] Done.
Validation 9, 13 remaining
[2021-11-02 09:21:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:45] Number of windows considered: 1...
[2021-11-02 09:21:45] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:21:45] Done.
Validation 10, 12 remaining
[2021-11-02 09:21:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:46] Number of windows considered: 1...
[2021-11-02 09:21:46] Bias-correcting 1 members separately...
[2021-11-02 09:21:46] Done.
Validation 11, 11 remaining
[2021-11-02 09:21:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:47] Number of windows considered: 1...
[2021-11-02 09:21:47] Bias-correcting 1 members separately...
[2021-11-02 09:21:47] Done.
Validation 12, 10 remaining
[2021-11-02 09:21:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:48] Number of windows considered: 1...
[2021-11-02 09:21:48] Bias-correcting 1 members separately...
[2021-11-02 09:21:48] Done.
Validation 13, 9 remaining
[2021-11-02 09:21:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:48] Number of windows considered: 1...
[2021-11-02 09:21:48] Bias-correcting 1 members separately...
[2021-11-02 09:21:48] Done.
Validation 14, 8 remaining
[2021-11-02 09:21:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:49] Number of windows considered: 1...
[2021-11-02 09:21:49] Bias-correcting 1 members separately...
[2021-11-02 09:21:49] Done.
Validation 15, 7 remaining
[2021-11-02 09:21:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:50] Number of windows considered: 1...
[2021-11-02 09:21:50] Bias-correcting 1 members separately...
[2021-11-02 09:21:50] Done.
Validation 16, 6 remaining
[2021-11-02 09:21:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:51] Number of windows considered: 1...
[2021-11-02 09:21:51] Bias-correcting 1 members separately...
[2021-11-02 09:21:51] Done.
Validation 17, 5 remaining
[2021-11-02 09:21:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:52] Number of windows considered: 1...
[2021-11-02 09:21:52] Bias-correcting 1 members separately...
[2021-11-02 09:21:52] Done.
Validation 18, 4 remaining
[2021-11-02 09:21:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:52] Number of windows considered: 1...
[2021-11-02 09:21:52] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:21:52] Done.
Validation 19, 3 remaining
[2021-11-02 09:21:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:53] Number of windows considered: 1...
[2021-11-02 09:21:53] Bias-correcting 1 members separately...
[2021-11-02 09:21:53] Done.
Validation 20, 2 remaining
[2021-11-02 09:21:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:54] Number of windows considered: 1...
[2021-11-02 09:21:54] Bias-correcting 1 members separately...
[2021-11-02 09:21:54] Done.
Validation 21, 1 remaining
[2021-11-02 09:21:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:55] Number of windows considered: 1...
[2021-11-02 09:21:55] Bias-correcting 1 members separately...
[2021-11-02 09:21:55] Done.
Validation 22, 0 remaining
[2021-11-02 09:21:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:21:55] Number of windows considered: 1...
[2021-11-02 09:21:55] Bias-correcting 1 members separately...
[2021-11-02 09:21:56] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-11-02 09:21:56] Performing annual aggregation...
[2021-11-02 09:21:56] Done.
[2021-11-02 09:21:56] - Computing climatology...
[2021-11-02 09:21:56] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:22:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:14] Number of windows considered: 1...
[2021-11-02 09:22:14] Bias-correcting 1 members separately...
[2021-11-02 09:22:14] Done.
Validation 2, 20 remaining
[2021-11-02 09:22:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:15] Number of windows considered: 1...
[2021-11-02 09:22:15] Bias-correcting 1 members separately...
[2021-11-02 09:22:15] Done.
Validation 3, 19 remaining
[2021-11-02 09:22:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:16] Number of windows considered: 1...
[2021-11-02 09:22:16] Bias-correcting 1 members separately...
[2021-11-02 09:22:16] Done.
Validation 4, 18 remaining
[2021-11-02 09:22:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:16] Number of windows considered: 1...
[2021-11-02 09:22:16] Bias-correcting 1 members separately...
[2021-11-02 09:22:16] Done.
Validation 5, 17 remaining
[2021-11-02 09:22:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:17] Number of windows considered: 1...
[2021-11-02 09:22:17] Bias-correcting 1 members separately...
[2021-11-02 09:22:17] Done.
Validation 6, 16 remaining
[2021-11-02 09:22:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:18] Number of windows considered: 1...
[2021-11-02 09:22:18] Bias-correcting 1 members separately...
[2021-11-02 09:22:18] Done.
Validation 7, 15 remaining
[2021-11-02 09:22:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:18] Number of windows considered: 1...
[2021-11-02 09:22:18] Bias-correcting 1 members separately...
[2021-11-02 09:22:18] Done.
Validation 8, 14 remaining
[2021-11-02 09:22:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:19] Number of windows considered: 1...
[2021-11-02 09:22:19] Bias-correcting 1 members separately...
[2021-11-02 09:22:19] Done.
Validation 9, 13 remaining
[2021-11-02 09:22:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:20] Number of windows considered: 1...
[2021-11-02 09:22:20] Bias-correcting 1 members separately...
[2021-11-02 09:22:20] Done.
Validation 10, 12 remaining
[2021-11-02 09:22:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:20] Number of windows considered: 1...
[2021-11-02 09:22:20] Bias-correcting 1 members separately...
[2021-11-02 09:22:20] Done.
Validation 11, 11 remaining
[2021-11-02 09:22:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:21] Number of windows considered: 1...
[2021-11-02 09:22:21] Bias-correcting 1 members separately...
[2021-11-02 09:22:21] Done.
Validation 12, 10 remaining
[2021-11-02 09:22:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:22] Number of windows considered: 1...
[2021-11-02 09:22:22] Bias-correcting 1 members separately...
[2021-11-02 09:22:22] Done.
Validation 13, 9 remaining
[2021-11-02 09:22:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:23] Number of windows considered: 1...
[2021-11-02 09:22:23] Bias-correcting 1 members separately...
[2021-11-02 09:22:23] Done.
Validation 14, 8 remaining
[2021-11-02 09:22:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:23] Number of windows considered: 1...
[2021-11-02 09:22:23] Bias-correcting 1 members separately...
[2021-11-02 09:22:23] Done.
Validation 15, 7 remaining
[2021-11-02 09:22:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:24] Number of windows considered: 1...
[2021-11-02 09:22:24] Bias-correcting 1 members separately...
[2021-11-02 09:22:24] Done.
Validation 16, 6 remaining
[2021-11-02 09:22:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:25] Number of windows considered: 1...
[2021-11-02 09:22:25] Bias-correcting 1 members separately...
[2021-11-02 09:22:25] Done.
Validation 17, 5 remaining
[2021-11-02 09:22:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:25] Number of windows considered: 1...
[2021-11-02 09:22:25] Bias-correcting 1 members separately...
[2021-11-02 09:22:25] Done.
Validation 18, 4 remaining
[2021-11-02 09:22:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:26] Number of windows considered: 1...
[2021-11-02 09:22:26] Bias-correcting 1 members separately...
[2021-11-02 09:22:26] Done.
Validation 19, 3 remaining
[2021-11-02 09:22:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:27] Number of windows considered: 1...
[2021-11-02 09:22:27] Bias-correcting 1 members separately...
[2021-11-02 09:22:27] Done.
Validation 20, 2 remaining
[2021-11-02 09:22:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:28] Number of windows considered: 1...
[2021-11-02 09:22:28] Bias-correcting 1 members separately...
[2021-11-02 09:22:28] Done.
Validation 21, 1 remaining
[2021-11-02 09:22:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:28] Number of windows considered: 1...
[2021-11-02 09:22:28] Bias-correcting 1 members separately...
[2021-11-02 09:22:28] Done.
Validation 22, 0 remaining
[2021-11-02 09:22:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:29] Number of windows considered: 1...
[2021-11-02 09:22:29] Bias-correcting 1 members separately...
[2021-11-02 09:22:29] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-11-02 09:22:29] Performing annual aggregation...
[2021-11-02 09:22:29] Done.
[2021-11-02 09:22:29] - Computing climatology...
[2021-11-02 09:22:29] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm2.cl4 <- index.cal.station.cl4
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)
scores
GPQM2-WT4 PQM-WT4 EQM-WT4 GPQM-WT4
0.7150858 0.6530402 0.6162920 0.3471750
scores.st1.wt4 <- scores
WT5
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))
station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
[2021-11-02 09:22:49] Performing annual aggregation...
[2021-11-02 09:22:49] Done.
[2021-11-02 09:22:49] - Computing climatology...
[2021-11-02 09:22:49] - Done.
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)
index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
[2021-11-02 09:22:49] Performing annual aggregation...
[2021-11-02 09:22:49] Done.
[2021-11-02 09:22:49] - Computing climatology...
[2021-11-02 09:22:49] - Done.
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")
station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:22:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:53] Number of windows considered: 1...
[2021-11-02 09:22:53] Bias-correcting 1 members separately...
[2021-11-02 09:22:53] Done.
Validation 2, 20 remaining
[2021-11-02 09:22:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:54] Number of windows considered: 1...
[2021-11-02 09:22:54] Bias-correcting 1 members separately...
[2021-11-02 09:22:54] Done.
Validation 3, 19 remaining
[2021-11-02 09:22:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:55] Number of windows considered: 1...
[2021-11-02 09:22:55] Bias-correcting 1 members separately...
[2021-11-02 09:22:55] Done.
Validation 4, 18 remaining
[2021-11-02 09:22:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:56] Number of windows considered: 1...
[2021-11-02 09:22:56] Bias-correcting 1 members separately...
[2021-11-02 09:22:56] Done.
Validation 5, 17 remaining
[2021-11-02 09:22:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:56] Number of windows considered: 1...
[2021-11-02 09:22:56] Bias-correcting 1 members separately...
[2021-11-02 09:22:56] Done.
Validation 6, 16 remaining
[2021-11-02 09:22:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:57] Number of windows considered: 1...
[2021-11-02 09:22:57] Bias-correcting 1 members separately...
[2021-11-02 09:22:57] Done.
Validation 7, 15 remaining
[2021-11-02 09:22:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:58] Number of windows considered: 1...
[2021-11-02 09:22:58] Bias-correcting 1 members separately...
[2021-11-02 09:22:58] Done.
Validation 8, 14 remaining
[2021-11-02 09:22:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:58] Number of windows considered: 1...
[2021-11-02 09:22:58] Bias-correcting 1 members separately...
[2021-11-02 09:22:59] Done.
Validation 9, 13 remaining
[2021-11-02 09:22:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:22:59] Number of windows considered: 1...
[2021-11-02 09:22:59] Bias-correcting 1 members separately...
[2021-11-02 09:22:59] Done.
Validation 10, 12 remaining
[2021-11-02 09:23:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:00] Number of windows considered: 1...
[2021-11-02 09:23:00] Bias-correcting 1 members separately...
[2021-11-02 09:23:00] Done.
Validation 11, 11 remaining
[2021-11-02 09:23:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:01] Number of windows considered: 1...
[2021-11-02 09:23:01] Bias-correcting 1 members separately...
[2021-11-02 09:23:01] Done.
Validation 12, 10 remaining
[2021-11-02 09:23:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:01] Number of windows considered: 1...
[2021-11-02 09:23:01] Bias-correcting 1 members separately...
[2021-11-02 09:23:02] Done.
Validation 13, 9 remaining
[2021-11-02 09:23:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:02] Number of windows considered: 1...
[2021-11-02 09:23:02] Bias-correcting 1 members separately...
[2021-11-02 09:23:02] Done.
Validation 14, 8 remaining
[2021-11-02 09:23:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:03] Number of windows considered: 1...
[2021-11-02 09:23:03] Bias-correcting 1 members separately...
[2021-11-02 09:23:03] Done.
Validation 15, 7 remaining
[2021-11-02 09:23:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:04] Number of windows considered: 1...
[2021-11-02 09:23:04] Bias-correcting 1 members separately...
[2021-11-02 09:23:04] Done.
Validation 16, 6 remaining
[2021-11-02 09:23:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:04] Number of windows considered: 1...
[2021-11-02 09:23:04] Bias-correcting 1 members separately...
[2021-11-02 09:23:04] Done.
Validation 17, 5 remaining
[2021-11-02 09:23:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:05] Number of windows considered: 1...
[2021-11-02 09:23:05] Bias-correcting 1 members separately...
[2021-11-02 09:23:05] Done.
Validation 18, 4 remaining
[2021-11-02 09:23:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:05] Number of windows considered: 1...
[2021-11-02 09:23:05] Bias-correcting 1 members separately...
[2021-11-02 09:23:05] Done.
Validation 19, 3 remaining
[2021-11-02 09:23:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:06] Number of windows considered: 1...
[2021-11-02 09:23:06] Bias-correcting 1 members separately...
[2021-11-02 09:23:06] Done.
Validation 20, 2 remaining
[2021-11-02 09:23:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:07] Number of windows considered: 1...
[2021-11-02 09:23:07] Bias-correcting 1 members separately...
[2021-11-02 09:23:07] Done.
Validation 21, 1 remaining
[2021-11-02 09:23:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:07] Number of windows considered: 1...
[2021-11-02 09:23:07] Bias-correcting 1 members separately...
[2021-11-02 09:23:07] Done.
Validation 22, 0 remaining
[2021-11-02 09:23:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:08] Number of windows considered: 1...
[2021-11-02 09:23:08] Bias-correcting 1 members separately...
[2021-11-02 09:23:08] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-11-02 09:23:08] Performing annual aggregation...
[2021-11-02 09:23:08] Done.
[2021-11-02 09:23:08] - Computing climatology...
[2021-11-02 09:23:08] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.pqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:23:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:16] Number of windows considered: 1...
[2021-11-02 09:23:16] Bias-correcting 1 members separately...
[2021-11-02 09:23:17] Done.
Validation 2, 20 remaining
[2021-11-02 09:23:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:17] Number of windows considered: 1...
[2021-11-02 09:23:17] Bias-correcting 1 members separately...
[2021-11-02 09:23:17] Done.
Validation 3, 19 remaining
[2021-11-02 09:23:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:18] Number of windows considered: 1...
[2021-11-02 09:23:18] Bias-correcting 1 members separately...
[2021-11-02 09:23:18] Done.
Validation 4, 18 remaining
[2021-11-02 09:23:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:19] Number of windows considered: 1...
[2021-11-02 09:23:19] Bias-correcting 1 members separately...
[2021-11-02 09:23:19] Done.
Validation 5, 17 remaining
[2021-11-02 09:23:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:19] Number of windows considered: 1...
[2021-11-02 09:23:19] Bias-correcting 1 members separately...
[2021-11-02 09:23:19] Done.
Validation 6, 16 remaining
[2021-11-02 09:23:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:20] Number of windows considered: 1...
[2021-11-02 09:23:20] Bias-correcting 1 members separately...
[2021-11-02 09:23:20] Done.
Validation 7, 15 remaining
[2021-11-02 09:23:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:21] Number of windows considered: 1...
[2021-11-02 09:23:21] Bias-correcting 1 members separately...
[2021-11-02 09:23:21] Done.
Validation 8, 14 remaining
[2021-11-02 09:23:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:21] Number of windows considered: 1...
[2021-11-02 09:23:21] Bias-correcting 1 members separately...
[2021-11-02 09:23:22] Done.
Validation 9, 13 remaining
[2021-11-02 09:23:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:22] Number of windows considered: 1...
[2021-11-02 09:23:22] Bias-correcting 1 members separately...
[2021-11-02 09:23:22] Done.
Validation 10, 12 remaining
[2021-11-02 09:23:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:23] Number of windows considered: 1...
[2021-11-02 09:23:23] Bias-correcting 1 members separately...
[2021-11-02 09:23:23] Done.
Validation 11, 11 remaining
[2021-11-02 09:23:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:24] Number of windows considered: 1...
[2021-11-02 09:23:24] Bias-correcting 1 members separately...
[2021-11-02 09:23:24] Done.
Validation 12, 10 remaining
[2021-11-02 09:23:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:24] Number of windows considered: 1...
[2021-11-02 09:23:24] Bias-correcting 1 members separately...
[2021-11-02 09:23:24] Done.
Validation 13, 9 remaining
[2021-11-02 09:23:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:25] Number of windows considered: 1...
[2021-11-02 09:23:25] Bias-correcting 1 members separately...
[2021-11-02 09:23:25] Done.
Validation 14, 8 remaining
[2021-11-02 09:23:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:26] Number of windows considered: 1...
[2021-11-02 09:23:26] Bias-correcting 1 members separately...
[2021-11-02 09:23:26] Done.
Validation 15, 7 remaining
[2021-11-02 09:23:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:27] Number of windows considered: 1...
[2021-11-02 09:23:27] Bias-correcting 1 members separately...
[2021-11-02 09:23:27] Done.
Validation 16, 6 remaining
[2021-11-02 09:23:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:27] Number of windows considered: 1...
[2021-11-02 09:23:27] Bias-correcting 1 members separately...
[2021-11-02 09:23:27] Done.
Validation 17, 5 remaining
[2021-11-02 09:23:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:28] Number of windows considered: 1...
[2021-11-02 09:23:28] Bias-correcting 1 members separately...
[2021-11-02 09:23:28] Done.
Validation 18, 4 remaining
[2021-11-02 09:23:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:29] Number of windows considered: 1...
[2021-11-02 09:23:29] Bias-correcting 1 members separately...
[2021-11-02 09:23:29] Done.
Validation 19, 3 remaining
[2021-11-02 09:23:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:30] Number of windows considered: 1...
[2021-11-02 09:23:30] Bias-correcting 1 members separately...
[2021-11-02 09:23:30] Done.
Validation 20, 2 remaining
[2021-11-02 09:23:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:30] Number of windows considered: 1...
[2021-11-02 09:23:30] Bias-correcting 1 members separately...
[2021-11-02 09:23:31] Done.
Validation 21, 1 remaining
[2021-11-02 09:23:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:31] Number of windows considered: 1...
[2021-11-02 09:23:31] Bias-correcting 1 members separately...
[2021-11-02 09:23:31] Done.
Validation 22, 0 remaining
[2021-11-02 09:23:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:32] Number of windows considered: 1...
[2021-11-02 09:23:32] Bias-correcting 1 members separately...
[2021-11-02 09:23:32] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-11-02 09:23:33] Performing annual aggregation...
[2021-11-02 09:23:33] Done.
[2021-11-02 09:23:33] - Computing climatology...
[2021-11-02 09:23:33] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.eqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:23:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:43] Number of windows considered: 1...
[2021-11-02 09:23:43] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:43] Done.
Validation 2, 20 remaining
[2021-11-02 09:23:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:43] Number of windows considered: 1...
[2021-11-02 09:23:43] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:44] Done.
Validation 3, 19 remaining
[2021-11-02 09:23:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:44] Number of windows considered: 1...
[2021-11-02 09:23:44] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:44] Done.
Validation 4, 18 remaining
[2021-11-02 09:23:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:45] Number of windows considered: 1...
[2021-11-02 09:23:45] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:23:45] Done.
Validation 5, 17 remaining
[2021-11-02 09:23:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:46] Number of windows considered: 1...
[2021-11-02 09:23:46] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:46] Done.
Validation 6, 16 remaining
[2021-11-02 09:23:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:46] Number of windows considered: 1...
[2021-11-02 09:23:46] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:46] Done.
Validation 7, 15 remaining
[2021-11-02 09:23:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:47] Number of windows considered: 1...
[2021-11-02 09:23:47] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:23:47] Done.
Validation 8, 14 remaining
[2021-11-02 09:23:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:48] Number of windows considered: 1...
[2021-11-02 09:23:48] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:48] Done.
Validation 9, 13 remaining
[2021-11-02 09:23:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:48] Number of windows considered: 1...
[2021-11-02 09:23:48] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:48] Done.
Validation 10, 12 remaining
[2021-11-02 09:23:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:49] Number of windows considered: 1...
[2021-11-02 09:23:49] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:49] Done.
Validation 11, 11 remaining
[2021-11-02 09:23:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:50] Number of windows considered: 1...
[2021-11-02 09:23:50] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:50] Done.
Validation 12, 10 remaining
[2021-11-02 09:23:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:50] Number of windows considered: 1...
[2021-11-02 09:23:50] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:51] Done.
Validation 13, 9 remaining
[2021-11-02 09:23:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:51] Number of windows considered: 1...
[2021-11-02 09:23:51] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:51] Done.
Validation 14, 8 remaining
[2021-11-02 09:23:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:52] Number of windows considered: 1...
[2021-11-02 09:23:52] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:52] Done.
Validation 15, 7 remaining
[2021-11-02 09:23:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:53] Number of windows considered: 1...
[2021-11-02 09:23:53] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:53] Done.
Validation 16, 6 remaining
[2021-11-02 09:23:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:53] Number of windows considered: 1...
[2021-11-02 09:23:53] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:54] Done.
Validation 17, 5 remaining
[2021-11-02 09:23:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:54] Number of windows considered: 1...
[2021-11-02 09:23:54] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:23:54] Done.
Validation 18, 4 remaining
[2021-11-02 09:23:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:55] Number of windows considered: 1...
[2021-11-02 09:23:55] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:55] Done.
Validation 19, 3 remaining
[2021-11-02 09:23:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:56] Number of windows considered: 1...
[2021-11-02 09:23:56] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:23:56] Done.
Validation 20, 2 remaining
[2021-11-02 09:23:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:56] Number of windows considered: 1...
[2021-11-02 09:23:56] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:56] Done.
Validation 21, 1 remaining
[2021-11-02 09:23:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:57] Number of windows considered: 1...
[2021-11-02 09:23:57] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:23:57] Done.
Validation 22, 0 remaining
[2021-11-02 09:23:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:23:58] Number of windows considered: 1...
[2021-11-02 09:23:58] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:23:58] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-11-02 09:23:58] Performing annual aggregation...
[2021-11-02 09:23:58] Done.
[2021-11-02 09:23:58] - Computing climatology...
[2021-11-02 09:23:58] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:24:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:08] Number of windows considered: 1...
[2021-11-02 09:24:08] Bias-correcting 1 members separately...
[2021-11-02 09:24:08] Done.
Validation 2, 20 remaining
[2021-11-02 09:24:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:08] Number of windows considered: 1...
[2021-11-02 09:24:08] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 09:24:08] Done.
Validation 3, 19 remaining
[2021-11-02 09:24:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:09] Number of windows considered: 1...
[2021-11-02 09:24:09] Bias-correcting 1 members separately...
[2021-11-02 09:24:09] Done.
Validation 4, 18 remaining
[2021-11-02 09:24:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:10] Number of windows considered: 1...
[2021-11-02 09:24:10] Bias-correcting 1 members separately...
[2021-11-02 09:24:10] Done.
Validation 5, 17 remaining
[2021-11-02 09:24:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:10] Number of windows considered: 1...
[2021-11-02 09:24:10] Bias-correcting 1 members separately...
[2021-11-02 09:24:11] Done.
Validation 6, 16 remaining
[2021-11-02 09:24:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:11] Number of windows considered: 1...
[2021-11-02 09:24:11] Bias-correcting 1 members separately...
[2021-11-02 09:24:11] Done.
Validation 7, 15 remaining
[2021-11-02 09:24:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:12] Number of windows considered: 1...
[2021-11-02 09:24:12] Bias-correcting 1 members separately...
[2021-11-02 09:24:12] Done.
Validation 8, 14 remaining
[2021-11-02 09:24:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:13] Number of windows considered: 1...
[2021-11-02 09:24:13] Bias-correcting 1 members separately...
[2021-11-02 09:24:13] Done.
Validation 9, 13 remaining
[2021-11-02 09:24:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:14] Number of windows considered: 1...
[2021-11-02 09:24:14] Bias-correcting 1 members separately...
[2021-11-02 09:24:14] Done.
Validation 10, 12 remaining
[2021-11-02 09:24:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:14] Number of windows considered: 1...
[2021-11-02 09:24:14] Bias-correcting 1 members separately...
[2021-11-02 09:24:14] Done.
Validation 11, 11 remaining
[2021-11-02 09:24:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:15] Number of windows considered: 1...
[2021-11-02 09:24:15] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:24:15] Done.
Validation 12, 10 remaining
[2021-11-02 09:24:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:16] Number of windows considered: 1...
[2021-11-02 09:24:16] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 09:24:16] Done.
Validation 13, 9 remaining
[2021-11-02 09:24:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:16] Number of windows considered: 1...
[2021-11-02 09:24:16] Bias-correcting 1 members separately...
[2021-11-02 09:24:17] Done.
Validation 14, 8 remaining
[2021-11-02 09:24:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:17] Number of windows considered: 1...
[2021-11-02 09:24:17] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 09:24:17] Done.
Validation 15, 7 remaining
[2021-11-02 09:24:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:18] Number of windows considered: 1...
[2021-11-02 09:24:18] Bias-correcting 1 members separately...
[2021-11-02 09:24:18] Done.
Validation 16, 6 remaining
[2021-11-02 09:24:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:19] Number of windows considered: 1...
[2021-11-02 09:24:19] Bias-correcting 1 members separately...
[2021-11-02 09:24:19] Done.
Validation 17, 5 remaining
[2021-11-02 09:24:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:20] Number of windows considered: 1...
[2021-11-02 09:24:20] Bias-correcting 1 members separately...
[2021-11-02 09:24:20] Done.
Validation 18, 4 remaining
[2021-11-02 09:24:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:20] Number of windows considered: 1...
[2021-11-02 09:24:20] Bias-correcting 1 members separately...
[2021-11-02 09:24:20] Done.
Validation 19, 3 remaining
[2021-11-02 09:24:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:21] Number of windows considered: 1...
[2021-11-02 09:24:21] Bias-correcting 1 members separately...
[2021-11-02 09:24:21] Done.
Validation 20, 2 remaining
[2021-11-02 09:24:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:22] Number of windows considered: 1...
[2021-11-02 09:24:22] Bias-correcting 1 members separately...
[2021-11-02 09:24:22] Done.
Validation 21, 1 remaining
[2021-11-02 09:24:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:23] Number of windows considered: 1...
[2021-11-02 09:24:23] Bias-correcting 1 members separately...
[2021-11-02 09:24:23] Done.
Validation 22, 0 remaining
[2021-11-02 09:24:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:23] Number of windows considered: 1...
[2021-11-02 09:24:23] Bias-correcting 1 members separately...
[2021-11-02 09:24:23] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-11-02 09:24:24] Performing annual aggregation...
[2021-11-02 09:24:24] Done.
[2021-11-02 09:24:24] - Computing climatology...
[2021-11-02 09:24:24] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm2.cl5 <- index.cal.station.cl5
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
PQM-WT5 EQM-WT5 GPQM2-WT5 GPQM-WT5
0.6518455 0.5762793 0.5238729 0.2928963
scores.st1.wt5 <- scores
Complete period (WO WTs)
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
[2021-11-02 09:24:46] Performing annual aggregation...
[2021-11-02 09:24:46] Done.
[2021-11-02 09:24:46] - Computing climatology...
[2021-11-02 09:24:46] - Done.
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)
index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
[2021-11-02 09:24:46] Performing annual aggregation...
[2021-11-02 09:24:46] Done.
[2021-11-02 09:24:46] - Computing climatology...
[2021-11-02 09:24:46] - Done.
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "pqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-11-02 09:24:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:51] Number of windows considered: 1...
[2021-11-02 09:24:51] Bias-correcting 1 members separately...
[2021-11-02 09:24:51] Done.
Validation 2, 20 remaining
[2021-11-02 09:24:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:52] Number of windows considered: 1...
[2021-11-02 09:24:52] Bias-correcting 1 members separately...
[2021-11-02 09:24:52] Done.
Validation 3, 19 remaining
[2021-11-02 09:24:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:52] Number of windows considered: 1...
[2021-11-02 09:24:52] Bias-correcting 1 members separately...
[2021-11-02 09:24:52] Done.
Validation 4, 18 remaining
[2021-11-02 09:24:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:53] Number of windows considered: 1...
[2021-11-02 09:24:53] Bias-correcting 1 members separately...
[2021-11-02 09:24:53] Done.
Validation 5, 17 remaining
[2021-11-02 09:24:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:54] Number of windows considered: 1...
[2021-11-02 09:24:54] Bias-correcting 1 members separately...
[2021-11-02 09:24:54] Done.
Validation 6, 16 remaining
[2021-11-02 09:24:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:54] Number of windows considered: 1...
[2021-11-02 09:24:54] Bias-correcting 1 members separately...
[2021-11-02 09:24:54] Done.
Validation 7, 15 remaining
[2021-11-02 09:24:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:55] Number of windows considered: 1...
[2021-11-02 09:24:55] Bias-correcting 1 members separately...
[2021-11-02 09:24:55] Done.
Validation 8, 14 remaining
[2021-11-02 09:24:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:55] Number of windows considered: 1...
[2021-11-02 09:24:55] Bias-correcting 1 members separately...
[2021-11-02 09:24:56] Done.
Validation 9, 13 remaining
[2021-11-02 09:24:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:56] Number of windows considered: 1...
[2021-11-02 09:24:56] Bias-correcting 1 members separately...
[2021-11-02 09:24:56] Done.
Validation 10, 12 remaining
[2021-11-02 09:24:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:57] Number of windows considered: 1...
[2021-11-02 09:24:57] Bias-correcting 1 members separately...
[2021-11-02 09:24:57] Done.
Validation 11, 11 remaining
[2021-11-02 09:24:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:57] Number of windows considered: 1...
[2021-11-02 09:24:57] Bias-correcting 1 members separately...
[2021-11-02 09:24:57] Done.
Validation 12, 10 remaining
[2021-11-02 09:24:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:58] Number of windows considered: 1...
[2021-11-02 09:24:58] Bias-correcting 1 members separately...
[2021-11-02 09:24:58] Done.
Validation 13, 9 remaining
[2021-11-02 09:24:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:24:59] Number of windows considered: 1...
[2021-11-02 09:24:59] Bias-correcting 1 members separately...
[2021-11-02 09:24:59] Done.
Validation 14, 8 remaining
[2021-11-02 09:25:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:00] Number of windows considered: 1...
[2021-11-02 09:25:00] Bias-correcting 1 members separately...
[2021-11-02 09:25:00] Done.
Validation 15, 7 remaining
[2021-11-02 09:25:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:00] Number of windows considered: 1...
[2021-11-02 09:25:00] Bias-correcting 1 members separately...
[2021-11-02 09:25:00] Done.
Validation 16, 6 remaining
[2021-11-02 09:25:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:01] Number of windows considered: 1...
[2021-11-02 09:25:01] Bias-correcting 1 members separately...
[2021-11-02 09:25:01] Done.
Validation 17, 5 remaining
[2021-11-02 09:25:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:02] Number of windows considered: 1...
[2021-11-02 09:25:02] Bias-correcting 1 members separately...
[2021-11-02 09:25:02] Done.
Validation 18, 4 remaining
[2021-11-02 09:25:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:02] Number of windows considered: 1...
[2021-11-02 09:25:02] Bias-correcting 1 members separately...
[2021-11-02 09:25:02] Done.
Validation 19, 3 remaining
[2021-11-02 09:25:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:03] Number of windows considered: 1...
[2021-11-02 09:25:03] Bias-correcting 1 members separately...
[2021-11-02 09:25:03] Done.
Validation 20, 2 remaining
[2021-11-02 09:25:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:04] Number of windows considered: 1...
[2021-11-02 09:25:04] Bias-correcting 1 members separately...
[2021-11-02 09:25:04] Done.
Validation 21, 1 remaining
[2021-11-02 09:25:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:05] Number of windows considered: 1...
[2021-11-02 09:25:05] Bias-correcting 1 members separately...
[2021-11-02 09:25:05] Done.
Validation 22, 0 remaining
[2021-11-02 09:25:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:05] Number of windows considered: 1...
[2021-11-02 09:25:05] Bias-correcting 1 members separately...
[2021-11-02 09:25:05] Done.
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 09:25:06] Performing annual aggregation...
[2021-11-02 09:25:06] Done.
[2021-11-02 09:25:06] - Computing climatology...
[2021-11-02 09:25:06] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.pqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "eqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-11-02 09:25:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:22] Number of windows considered: 1...
[2021-11-02 09:25:22] Bias-correcting 1 members separately...
[2021-11-02 09:25:22] Done.
Validation 2, 20 remaining
[2021-11-02 09:25:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:23] Number of windows considered: 1...
[2021-11-02 09:25:23] Bias-correcting 1 members separately...
[2021-11-02 09:25:23] Done.
Validation 3, 19 remaining
[2021-11-02 09:25:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:24] Number of windows considered: 1...
[2021-11-02 09:25:24] Bias-correcting 1 members separately...
[2021-11-02 09:25:24] Done.
Validation 4, 18 remaining
[2021-11-02 09:25:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:24] Number of windows considered: 1...
[2021-11-02 09:25:24] Bias-correcting 1 members separately...
[2021-11-02 09:25:24] Done.
Validation 5, 17 remaining
[2021-11-02 09:25:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:25] Number of windows considered: 1...
[2021-11-02 09:25:25] Bias-correcting 1 members separately...
[2021-11-02 09:25:25] Done.
Validation 6, 16 remaining
[2021-11-02 09:25:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:26] Number of windows considered: 1...
[2021-11-02 09:25:26] Bias-correcting 1 members separately...
[2021-11-02 09:25:26] Done.
Validation 7, 15 remaining
[2021-11-02 09:25:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:27] Number of windows considered: 1...
[2021-11-02 09:25:27] Bias-correcting 1 members separately...
[2021-11-02 09:25:27] Done.
Validation 8, 14 remaining
[2021-11-02 09:25:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:27] Number of windows considered: 1...
[2021-11-02 09:25:27] Bias-correcting 1 members separately...
[2021-11-02 09:25:27] Done.
Validation 9, 13 remaining
[2021-11-02 09:25:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:28] Number of windows considered: 1...
[2021-11-02 09:25:28] Bias-correcting 1 members separately...
[2021-11-02 09:25:28] Done.
Validation 10, 12 remaining
[2021-11-02 09:25:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:29] Number of windows considered: 1...
[2021-11-02 09:25:29] Bias-correcting 1 members separately...
[2021-11-02 09:25:29] Done.
Validation 11, 11 remaining
[2021-11-02 09:25:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:30] Number of windows considered: 1...
[2021-11-02 09:25:30] Bias-correcting 1 members separately...
[2021-11-02 09:25:30] Done.
Validation 12, 10 remaining
[2021-11-02 09:25:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:31] Number of windows considered: 1...
[2021-11-02 09:25:31] Bias-correcting 1 members separately...
[2021-11-02 09:25:31] Done.
Validation 13, 9 remaining
[2021-11-02 09:25:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:31] Number of windows considered: 1...
[2021-11-02 09:25:31] Bias-correcting 1 members separately...
[2021-11-02 09:25:32] Done.
Validation 14, 8 remaining
[2021-11-02 09:25:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:32] Number of windows considered: 1...
[2021-11-02 09:25:32] Bias-correcting 1 members separately...
[2021-11-02 09:25:32] Done.
Validation 15, 7 remaining
[2021-11-02 09:25:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:33] Number of windows considered: 1...
[2021-11-02 09:25:33] Bias-correcting 1 members separately...
[2021-11-02 09:25:33] Done.
Validation 16, 6 remaining
[2021-11-02 09:25:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:34] Number of windows considered: 1...
[2021-11-02 09:25:34] Bias-correcting 1 members separately...
[2021-11-02 09:25:34] Done.
Validation 17, 5 remaining
[2021-11-02 09:25:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:35] Number of windows considered: 1...
[2021-11-02 09:25:35] Bias-correcting 1 members separately...
[2021-11-02 09:25:35] Done.
Validation 18, 4 remaining
[2021-11-02 09:25:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:35] Number of windows considered: 1...
[2021-11-02 09:25:35] Bias-correcting 1 members separately...
[2021-11-02 09:25:35] Done.
Validation 19, 3 remaining
[2021-11-02 09:25:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:36] Number of windows considered: 1...
[2021-11-02 09:25:36] Bias-correcting 1 members separately...
[2021-11-02 09:25:36] Done.
Validation 20, 2 remaining
[2021-11-02 09:25:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:37] Number of windows considered: 1...
[2021-11-02 09:25:37] Bias-correcting 1 members separately...
[2021-11-02 09:25:37] Done.
Validation 21, 1 remaining
[2021-11-02 09:25:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:37] Number of windows considered: 1...
[2021-11-02 09:25:37] Bias-correcting 1 members separately...
[2021-11-02 09:25:37] Done.
Validation 22, 0 remaining
[2021-11-02 09:25:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:25:38] Number of windows considered: 1...
[2021-11-02 09:25:38] Bias-correcting 1 members separately...
[2021-11-02 09:25:38] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 09:25:38] Performing annual aggregation...
[2021-11-02 09:25:38] Done.
[2021-11-02 09:25:38] - Computing climatology...
[2021-11-02 09:25:38] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.eqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", cross.val = "loo")
Validation 1, 21 remaining
[2021-11-02 09:26:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:36] Number of windows considered: 1...
[2021-11-02 09:26:36] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:36] Done.
Validation 2, 20 remaining
[2021-11-02 09:26:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:36] Number of windows considered: 1...
[2021-11-02 09:26:36] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:37] Done.
Validation 3, 19 remaining
[2021-11-02 09:26:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:37] Number of windows considered: 1...
[2021-11-02 09:26:37] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:38] Done.
Validation 4, 18 remaining
[2021-11-02 09:26:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:38] Number of windows considered: 1...
[2021-11-02 09:26:38] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:39] Done.
Validation 5, 17 remaining
[2021-11-02 09:26:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:39] Number of windows considered: 1...
[2021-11-02 09:26:39] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:39] Done.
Validation 6, 16 remaining
[2021-11-02 09:26:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:40] Number of windows considered: 1...
[2021-11-02 09:26:40] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:40] Done.
Validation 7, 15 remaining
[2021-11-02 09:26:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:41] Number of windows considered: 1...
[2021-11-02 09:26:41] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:41] Done.
Validation 8, 14 remaining
[2021-11-02 09:26:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:42] Number of windows considered: 1...
[2021-11-02 09:26:42] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:42] Done.
Validation 9, 13 remaining
[2021-11-02 09:26:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:43] Number of windows considered: 1...
[2021-11-02 09:26:43] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:43] Done.
Validation 10, 12 remaining
[2021-11-02 09:26:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:44] Number of windows considered: 1...
[2021-11-02 09:26:44] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:44] Done.
Validation 11, 11 remaining
[2021-11-02 09:26:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:45] Number of windows considered: 1...
[2021-11-02 09:26:45] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:45] Done.
Validation 12, 10 remaining
[2021-11-02 09:26:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:46] Number of windows considered: 1...
[2021-11-02 09:26:46] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:46] Done.
Validation 13, 9 remaining
[2021-11-02 09:26:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:47] Number of windows considered: 1...
[2021-11-02 09:26:47] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:47] Done.
Validation 14, 8 remaining
[2021-11-02 09:26:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:48] Number of windows considered: 1...
[2021-11-02 09:26:48] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:48] Done.
Validation 15, 7 remaining
[2021-11-02 09:26:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:49] Number of windows considered: 1...
[2021-11-02 09:26:49] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:49] Done.
Validation 16, 6 remaining
[2021-11-02 09:26:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:50] Number of windows considered: 1...
[2021-11-02 09:26:50] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:50] Done.
Validation 17, 5 remaining
[2021-11-02 09:26:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:51] Number of windows considered: 1...
[2021-11-02 09:26:51] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:51] Done.
Validation 18, 4 remaining
[2021-11-02 09:26:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:52] Number of windows considered: 1...
[2021-11-02 09:26:52] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:52] Done.
Validation 19, 3 remaining
[2021-11-02 09:26:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:52] Number of windows considered: 1...
[2021-11-02 09:26:52] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:53] Done.
Validation 20, 2 remaining
[2021-11-02 09:26:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:54] Number of windows considered: 1...
[2021-11-02 09:26:54] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:54] Done.
Validation 21, 1 remaining
[2021-11-02 09:26:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:54] Number of windows considered: 1...
[2021-11-02 09:26:54] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:55] Done.
Validation 22, 0 remaining
[2021-11-02 09:26:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:26:56] Number of windows considered: 1...
[2021-11-02 09:26:56] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 09:26:56] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 09:26:56] Performing annual aggregation...
[2021-11-02 09:26:56] Done.
[2021-11-02 09:26:56] - Computing climatology...
[2021-11-02 09:26:56] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", theta = .7, cross.val = "loo")
Validation 1, 21 remaining
[2021-11-02 09:27:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:07] Number of windows considered: 1...
[2021-11-02 09:27:07] Bias-correcting 1 members separately...
[2021-11-02 09:27:08] Done.
Validation 2, 20 remaining
[2021-11-02 09:27:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:08] Number of windows considered: 1...
[2021-11-02 09:27:08] Bias-correcting 1 members separately...
[2021-11-02 09:27:08] Done.
Validation 3, 19 remaining
[2021-11-02 09:27:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:09] Number of windows considered: 1...
[2021-11-02 09:27:09] Bias-correcting 1 members separately...
[2021-11-02 09:27:09] Done.
Validation 4, 18 remaining
[2021-11-02 09:27:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:10] Number of windows considered: 1...
[2021-11-02 09:27:10] Bias-correcting 1 members separately...
[2021-11-02 09:27:10] Done.
Validation 5, 17 remaining
[2021-11-02 09:27:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:11] Number of windows considered: 1...
[2021-11-02 09:27:11] Bias-correcting 1 members separately...
[2021-11-02 09:27:11] Done.
Validation 6, 16 remaining
[2021-11-02 09:27:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:12] Number of windows considered: 1...
[2021-11-02 09:27:12] Bias-correcting 1 members separately...
[2021-11-02 09:27:12] Done.
Validation 7, 15 remaining
[2021-11-02 09:27:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:13] Number of windows considered: 1...
[2021-11-02 09:27:13] Bias-correcting 1 members separately...
[2021-11-02 09:27:13] Done.
Validation 8, 14 remaining
[2021-11-02 09:27:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:14] Number of windows considered: 1...
[2021-11-02 09:27:14] Bias-correcting 1 members separately...
[2021-11-02 09:27:14] Done.
Validation 9, 13 remaining
[2021-11-02 09:27:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:14] Number of windows considered: 1...
[2021-11-02 09:27:14] Bias-correcting 1 members separately...
[2021-11-02 09:27:15] Done.
Validation 10, 12 remaining
[2021-11-02 09:27:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:15] Number of windows considered: 1...
[2021-11-02 09:27:15] Bias-correcting 1 members separately...
[2021-11-02 09:27:15] Done.
Validation 11, 11 remaining
[2021-11-02 09:27:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:16] Number of windows considered: 1...
[2021-11-02 09:27:16] Bias-correcting 1 members separately...
[2021-11-02 09:27:16] Done.
Validation 12, 10 remaining
[2021-11-02 09:27:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:17] Number of windows considered: 1...
[2021-11-02 09:27:17] Bias-correcting 1 members separately...
[2021-11-02 09:27:17] Done.
Validation 13, 9 remaining
[2021-11-02 09:27:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:17] Number of windows considered: 1...
[2021-11-02 09:27:17] Bias-correcting 1 members separately...
[2021-11-02 09:27:17] Done.
Validation 14, 8 remaining
[2021-11-02 09:27:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:18] Number of windows considered: 1...
[2021-11-02 09:27:18] Bias-correcting 1 members separately...
[2021-11-02 09:27:18] Done.
Validation 15, 7 remaining
[2021-11-02 09:27:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:19] Number of windows considered: 1...
[2021-11-02 09:27:19] Bias-correcting 1 members separately...
[2021-11-02 09:27:19] Done.
Validation 16, 6 remaining
[2021-11-02 09:27:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:20] Number of windows considered: 1...
[2021-11-02 09:27:20] Bias-correcting 1 members separately...
[2021-11-02 09:27:20] Done.
Validation 17, 5 remaining
[2021-11-02 09:27:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:20] Number of windows considered: 1...
[2021-11-02 09:27:20] Bias-correcting 1 members separately...
[2021-11-02 09:27:21] Done.
Validation 18, 4 remaining
[2021-11-02 09:27:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:21] Number of windows considered: 1...
[2021-11-02 09:27:21] Bias-correcting 1 members separately...
[2021-11-02 09:27:21] Done.
Validation 19, 3 remaining
[2021-11-02 09:27:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:22] Number of windows considered: 1...
[2021-11-02 09:27:22] Bias-correcting 1 members separately...
[2021-11-02 09:27:22] Done.
Validation 20, 2 remaining
[2021-11-02 09:27:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:23] Number of windows considered: 1...
[2021-11-02 09:27:23] Bias-correcting 1 members separately...
[2021-11-02 09:27:23] Done.
Validation 21, 1 remaining
[2021-11-02 09:27:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:24] Number of windows considered: 1...
[2021-11-02 09:27:24] Bias-correcting 1 members separately...
[2021-11-02 09:27:24] Done.
Validation 22, 0 remaining
[2021-11-02 09:27:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:27:24] Number of windows considered: 1...
[2021-11-02 09:27:24] Bias-correcting 1 members separately...
[2021-11-02 09:27:25] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 09:27:25] Performing annual aggregation...
[2021-11-02 09:27:25] Done.
[2021-11-02 09:27:25] - Computing climatology...
[2021-11-02 09:27:25] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm2.complete <- index.cal.station.complete
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.trmm.complete[i]-index.obs.complete[i]),abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
score.trmm <- c()
for (i in c(1:9)) {
score.trmm <- c(score.trmm, norm.vector[[i]][1])
}
score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][2])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][3])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][4])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][5])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
EQM-C GPQM2-C PQM-C GPQM-C TRMM
0.6800581 0.6001866 0.5602078 0.3992687 0.3476210
scores.complete <- scores
paste(names(scores.st1.wt1[1]),names(scores.st1.wt2[1]),names(scores.st1.wt3[1]),names(scores.st1.wt4[1]),names(scores.st1.wt5[1]), names(scores.complete[1]))
[1] "PQM-WT1 PQM-WT2 PQM-WT3 GPQM2-WT4 PQM-WT5 EQM-C"
Combination of techniques by WT
cal.station.cl1.pqm <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T )
Validation 1, 21 remaining
[2021-11-02 09:28:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:20] Number of windows considered: 1...
[2021-11-02 09:28:20] Bias-correcting 1 members separately...
[2021-11-02 09:28:20] Done.
Validation 2, 20 remaining
[2021-11-02 09:28:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:21] Number of windows considered: 1...
[2021-11-02 09:28:21] Bias-correcting 1 members separately...
[2021-11-02 09:28:21] Done.
Validation 3, 19 remaining
[2021-11-02 09:28:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:21] Number of windows considered: 1...
[2021-11-02 09:28:21] Bias-correcting 1 members separately...
[2021-11-02 09:28:21] Done.
Validation 4, 18 remaining
[2021-11-02 09:28:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:22] Number of windows considered: 1...
[2021-11-02 09:28:22] Bias-correcting 1 members separately...
[2021-11-02 09:28:22] Done.
Validation 5, 17 remaining
[2021-11-02 09:28:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:23] Number of windows considered: 1...
[2021-11-02 09:28:23] Bias-correcting 1 members separately...
[2021-11-02 09:28:23] Done.
Validation 6, 16 remaining
[2021-11-02 09:28:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:23] Number of windows considered: 1...
[2021-11-02 09:28:23] Bias-correcting 1 members separately...
[2021-11-02 09:28:23] Done.
Validation 7, 15 remaining
[2021-11-02 09:28:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:24] Number of windows considered: 1...
[2021-11-02 09:28:24] Bias-correcting 1 members separately...
[2021-11-02 09:28:24] Done.
Validation 8, 14 remaining
[2021-11-02 09:28:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:25] Number of windows considered: 1...
[2021-11-02 09:28:25] Bias-correcting 1 members separately...
[2021-11-02 09:28:25] Done.
Validation 9, 13 remaining
[2021-11-02 09:28:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:25] Number of windows considered: 1...
[2021-11-02 09:28:25] Bias-correcting 1 members separately...
[2021-11-02 09:28:25] Done.
Validation 10, 12 remaining
[2021-11-02 09:28:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:26] Number of windows considered: 1...
[2021-11-02 09:28:26] Bias-correcting 1 members separately...
[2021-11-02 09:28:26] Done.
Validation 11, 11 remaining
[2021-11-02 09:28:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:27] Number of windows considered: 1...
[2021-11-02 09:28:27] Bias-correcting 1 members separately...
[2021-11-02 09:28:27] Done.
Validation 12, 10 remaining
[2021-11-02 09:28:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:27] Number of windows considered: 1...
[2021-11-02 09:28:27] Bias-correcting 1 members separately...
[2021-11-02 09:28:27] Done.
Validation 13, 9 remaining
[2021-11-02 09:28:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:28] Number of windows considered: 1...
[2021-11-02 09:28:28] Bias-correcting 1 members separately...
[2021-11-02 09:28:28] Done.
Validation 14, 8 remaining
[2021-11-02 09:28:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:29] Number of windows considered: 1...
[2021-11-02 09:28:29] Bias-correcting 1 members separately...
[2021-11-02 09:28:29] Done.
Validation 15, 7 remaining
[2021-11-02 09:28:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:30] Number of windows considered: 1...
[2021-11-02 09:28:30] Bias-correcting 1 members separately...
[2021-11-02 09:28:30] Done.
Validation 16, 6 remaining
[2021-11-02 09:28:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:30] Number of windows considered: 1...
[2021-11-02 09:28:30] Bias-correcting 1 members separately...
[2021-11-02 09:28:30] Done.
Validation 17, 5 remaining
[2021-11-02 09:28:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:31] Number of windows considered: 1...
[2021-11-02 09:28:31] Bias-correcting 1 members separately...
[2021-11-02 09:28:31] Done.
Validation 18, 4 remaining
[2021-11-02 09:28:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:32] Number of windows considered: 1...
[2021-11-02 09:28:32] Bias-correcting 1 members separately...
[2021-11-02 09:28:32] Done.
Validation 19, 3 remaining
[2021-11-02 09:28:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:32] Number of windows considered: 1...
[2021-11-02 09:28:32] Bias-correcting 1 members separately...
[2021-11-02 09:28:32] Done.
Validation 20, 2 remaining
[2021-11-02 09:28:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:33] Number of windows considered: 1...
[2021-11-02 09:28:33] Bias-correcting 1 members separately...
[2021-11-02 09:28:33] Done.
Validation 21, 1 remaining
[2021-11-02 09:28:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:34] Number of windows considered: 1...
[2021-11-02 09:28:34] Bias-correcting 1 members separately...
[2021-11-02 09:28:34] Done.
Validation 22, 0 remaining
[2021-11-02 09:28:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:35] Number of windows considered: 1...
[2021-11-02 09:28:35] Bias-correcting 1 members separately...
[2021-11-02 09:28:35] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl1.pqm$Dates$start <- as.POSIXct(cal.station.cl1.pqm$Dates$start,tz = "GMT")
cal.station.cl1.pqm$Dates$end <- as.POSIXct(cal.station.cl1.pqm$Dates$end,tz = "GMT")
cal.station.cl2.pqm <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:28:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:36] Number of windows considered: 1...
[2021-11-02 09:28:36] Bias-correcting 1 members separately...
[2021-11-02 09:28:36] Done.
Validation 2, 20 remaining
[2021-11-02 09:28:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:37] Number of windows considered: 1...
[2021-11-02 09:28:37] Bias-correcting 1 members separately...
[2021-11-02 09:28:37] Done.
Validation 3, 19 remaining
[2021-11-02 09:28:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:37] Number of windows considered: 1...
[2021-11-02 09:28:37] Bias-correcting 1 members separately...
[2021-11-02 09:28:37] Done.
Validation 4, 18 remaining
[2021-11-02 09:28:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:38] Number of windows considered: 1...
[2021-11-02 09:28:38] Bias-correcting 1 members separately...
[2021-11-02 09:28:38] Done.
Validation 5, 17 remaining
[2021-11-02 09:28:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:39] Number of windows considered: 1...
[2021-11-02 09:28:39] Bias-correcting 1 members separately...
[2021-11-02 09:28:39] Done.
Validation 6, 16 remaining
[2021-11-02 09:28:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:40] Number of windows considered: 1...
[2021-11-02 09:28:40] Bias-correcting 1 members separately...
[2021-11-02 09:28:40] Done.
Validation 7, 15 remaining
[2021-11-02 09:28:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:40] Number of windows considered: 1...
[2021-11-02 09:28:40] Bias-correcting 1 members separately...
[2021-11-02 09:28:40] Done.
Validation 8, 14 remaining
[2021-11-02 09:28:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:41] Number of windows considered: 1...
[2021-11-02 09:28:41] Bias-correcting 1 members separately...
[2021-11-02 09:28:41] Done.
Validation 9, 13 remaining
[2021-11-02 09:28:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:42] Number of windows considered: 1...
[2021-11-02 09:28:42] Bias-correcting 1 members separately...
[2021-11-02 09:28:42] Done.
Validation 10, 12 remaining
[2021-11-02 09:28:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:43] Number of windows considered: 1...
[2021-11-02 09:28:43] Bias-correcting 1 members separately...
[2021-11-02 09:28:43] Done.
Validation 11, 11 remaining
[2021-11-02 09:28:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:43] Number of windows considered: 1...
[2021-11-02 09:28:43] Bias-correcting 1 members separately...
[2021-11-02 09:28:44] Done.
Validation 12, 10 remaining
[2021-11-02 09:28:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:44] Number of windows considered: 1...
[2021-11-02 09:28:44] Bias-correcting 1 members separately...
[2021-11-02 09:28:44] Done.
Validation 13, 9 remaining
[2021-11-02 09:28:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:45] Number of windows considered: 1...
[2021-11-02 09:28:45] Bias-correcting 1 members separately...
[2021-11-02 09:28:45] Done.
Validation 14, 8 remaining
[2021-11-02 09:28:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:46] Number of windows considered: 1...
[2021-11-02 09:28:46] Bias-correcting 1 members separately...
[2021-11-02 09:28:46] Done.
Validation 15, 7 remaining
[2021-11-02 09:28:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:46] Number of windows considered: 1...
[2021-11-02 09:28:46] Bias-correcting 1 members separately...
[2021-11-02 09:28:47] Done.
Validation 16, 6 remaining
[2021-11-02 09:28:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:47] Number of windows considered: 1...
[2021-11-02 09:28:47] Bias-correcting 1 members separately...
[2021-11-02 09:28:47] Done.
Validation 17, 5 remaining
[2021-11-02 09:28:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:48] Number of windows considered: 1...
[2021-11-02 09:28:48] Bias-correcting 1 members separately...
[2021-11-02 09:28:48] Done.
Validation 18, 4 remaining
[2021-11-02 09:28:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:49] Number of windows considered: 1...
[2021-11-02 09:28:49] Bias-correcting 1 members separately...
[2021-11-02 09:28:49] Done.
Validation 19, 3 remaining
[2021-11-02 09:28:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:49] Number of windows considered: 1...
[2021-11-02 09:28:49] Bias-correcting 1 members separately...
[2021-11-02 09:28:49] Done.
Validation 20, 2 remaining
[2021-11-02 09:28:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:50] Number of windows considered: 1...
[2021-11-02 09:28:50] Bias-correcting 1 members separately...
[2021-11-02 09:28:50] Done.
Validation 21, 1 remaining
[2021-11-02 09:28:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:51] Number of windows considered: 1...
[2021-11-02 09:28:51] Bias-correcting 1 members separately...
[2021-11-02 09:28:51] Done.
Validation 22, 0 remaining
[2021-11-02 09:28:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:51] Number of windows considered: 1...
[2021-11-02 09:28:51] Bias-correcting 1 members separately...
[2021-11-02 09:28:51] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl2.pqm$Dates$start <- as.POSIXct(cal.station.cl2.pqm$Dates$start,tz = "GMT")
cal.station.cl2.pqm$Dates$end <- as.POSIXct(cal.station.cl2.pqm$Dates$end,tz = "GMT")
cal.station.cl3.pqm <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:28:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:52] Number of windows considered: 1...
[2021-11-02 09:28:52] Bias-correcting 1 members separately...
[2021-11-02 09:28:52] Done.
Validation 2, 20 remaining
[2021-11-02 09:28:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:53] Number of windows considered: 1...
[2021-11-02 09:28:53] Bias-correcting 1 members separately...
[2021-11-02 09:28:53] Done.
Validation 3, 19 remaining
[2021-11-02 09:28:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:54] Number of windows considered: 1...
[2021-11-02 09:28:54] Bias-correcting 1 members separately...
[2021-11-02 09:28:54] Done.
Validation 4, 18 remaining
[2021-11-02 09:28:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:54] Number of windows considered: 1...
[2021-11-02 09:28:54] Bias-correcting 1 members separately...
[2021-11-02 09:28:54] Done.
Validation 5, 17 remaining
[2021-11-02 09:28:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:55] Number of windows considered: 1...
[2021-11-02 09:28:55] Bias-correcting 1 members separately...
[2021-11-02 09:28:55] Done.
Validation 6, 16 remaining
[2021-11-02 09:28:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:56] Number of windows considered: 1...
[2021-11-02 09:28:56] Bias-correcting 1 members separately...
[2021-11-02 09:28:56] Done.
Validation 7, 15 remaining
[2021-11-02 09:28:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:56] Number of windows considered: 1...
[2021-11-02 09:28:56] Bias-correcting 1 members separately...
[2021-11-02 09:28:56] Done.
Validation 8, 14 remaining
[2021-11-02 09:28:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:57] Number of windows considered: 1...
[2021-11-02 09:28:57] Bias-correcting 1 members separately...
[2021-11-02 09:28:57] Done.
Validation 9, 13 remaining
[2021-11-02 09:28:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:58] Number of windows considered: 1...
[2021-11-02 09:28:58] Bias-correcting 1 members separately...
[2021-11-02 09:28:58] Done.
Validation 10, 12 remaining
[2021-11-02 09:28:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:58] Number of windows considered: 1...
[2021-11-02 09:28:58] Bias-correcting 1 members separately...
[2021-11-02 09:28:58] Done.
Validation 11, 11 remaining
[2021-11-02 09:28:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:28:59] Number of windows considered: 1...
[2021-11-02 09:28:59] Bias-correcting 1 members separately...
[2021-11-02 09:28:59] Done.
Validation 12, 10 remaining
[2021-11-02 09:29:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:00] Number of windows considered: 1...
[2021-11-02 09:29:00] Bias-correcting 1 members separately...
[2021-11-02 09:29:00] Done.
Validation 13, 9 remaining
[2021-11-02 09:29:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:00] Number of windows considered: 1...
[2021-11-02 09:29:00] Bias-correcting 1 members separately...
[2021-11-02 09:29:01] Done.
Validation 14, 8 remaining
[2021-11-02 09:29:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:01] Number of windows considered: 1...
[2021-11-02 09:29:01] Bias-correcting 1 members separately...
[2021-11-02 09:29:01] Done.
Validation 15, 7 remaining
[2021-11-02 09:29:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:02] Number of windows considered: 1...
[2021-11-02 09:29:02] Bias-correcting 1 members separately...
[2021-11-02 09:29:02] Done.
Validation 16, 6 remaining
[2021-11-02 09:29:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:03] Number of windows considered: 1...
[2021-11-02 09:29:03] Bias-correcting 1 members separately...
[2021-11-02 09:29:03] Done.
Validation 17, 5 remaining
[2021-11-02 09:29:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:03] Number of windows considered: 1...
[2021-11-02 09:29:03] Bias-correcting 1 members separately...
[2021-11-02 09:29:03] Done.
Validation 18, 4 remaining
[2021-11-02 09:29:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:04] Number of windows considered: 1...
[2021-11-02 09:29:04] Bias-correcting 1 members separately...
[2021-11-02 09:29:04] Done.
Validation 19, 3 remaining
[2021-11-02 09:29:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:05] Number of windows considered: 1...
[2021-11-02 09:29:05] Bias-correcting 1 members separately...
[2021-11-02 09:29:05] Done.
Validation 20, 2 remaining
[2021-11-02 09:29:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:05] Number of windows considered: 1...
[2021-11-02 09:29:05] Bias-correcting 1 members separately...
[2021-11-02 09:29:05] Done.
Validation 21, 1 remaining
[2021-11-02 09:29:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:06] Number of windows considered: 1...
[2021-11-02 09:29:06] Bias-correcting 1 members separately...
[2021-11-02 09:29:06] Done.
Validation 22, 0 remaining
[2021-11-02 09:29:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:07] Number of windows considered: 1...
[2021-11-02 09:29:07] Bias-correcting 1 members separately...
[2021-11-02 09:29:07] Done.
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl3.pqm$Dates$start <- as.POSIXct(cal.station.cl3.pqm$Dates$start,tz = "GMT")
cal.station.cl3.pqm$Dates$end <- as.POSIXct(cal.station.cl3.pqm$Dates$end,tz = "GMT")
cal.station.cl4.gpqm2 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm", theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:29:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:08] Number of windows considered: 1...
[2021-11-02 09:29:08] Bias-correcting 1 members separately...
[2021-11-02 09:29:08] Done.
Validation 2, 20 remaining
[2021-11-02 09:29:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:09] Number of windows considered: 1...
[2021-11-02 09:29:09] Bias-correcting 1 members separately...
[2021-11-02 09:29:09] Done.
Validation 3, 19 remaining
[2021-11-02 09:29:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:09] Number of windows considered: 1...
[2021-11-02 09:29:09] Bias-correcting 1 members separately...
[2021-11-02 09:29:10] Done.
Validation 4, 18 remaining
[2021-11-02 09:29:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:10] Number of windows considered: 1...
[2021-11-02 09:29:10] Bias-correcting 1 members separately...
[2021-11-02 09:29:10] Done.
Validation 5, 17 remaining
[2021-11-02 09:29:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:11] Number of windows considered: 1...
[2021-11-02 09:29:11] Bias-correcting 1 members separately...
[2021-11-02 09:29:11] Done.
Validation 6, 16 remaining
[2021-11-02 09:29:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:12] Number of windows considered: 1...
[2021-11-02 09:29:12] Bias-correcting 1 members separately...
[2021-11-02 09:29:12] Done.
Validation 7, 15 remaining
[2021-11-02 09:29:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:12] Number of windows considered: 1...
[2021-11-02 09:29:12] Bias-correcting 1 members separately...
[2021-11-02 09:29:13] Done.
Validation 8, 14 remaining
[2021-11-02 09:29:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:13] Number of windows considered: 1...
[2021-11-02 09:29:13] Bias-correcting 1 members separately...
[2021-11-02 09:29:13] Done.
Validation 9, 13 remaining
[2021-11-02 09:29:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:14] Number of windows considered: 1...
[2021-11-02 09:29:14] Bias-correcting 1 members separately...
[2021-11-02 09:29:14] Done.
Validation 10, 12 remaining
[2021-11-02 09:29:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:15] Number of windows considered: 1...
[2021-11-02 09:29:15] Bias-correcting 1 members separately...
[2021-11-02 09:29:15] Done.
Validation 11, 11 remaining
[2021-11-02 09:29:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:16] Number of windows considered: 1...
[2021-11-02 09:29:16] Bias-correcting 1 members separately...
[2021-11-02 09:29:16] Done.
Validation 12, 10 remaining
[2021-11-02 09:29:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:16] Number of windows considered: 1...
[2021-11-02 09:29:16] Bias-correcting 1 members separately...
[2021-11-02 09:29:16] Done.
Validation 13, 9 remaining
[2021-11-02 09:29:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:17] Number of windows considered: 1...
[2021-11-02 09:29:17] Bias-correcting 1 members separately...
[2021-11-02 09:29:17] Done.
Validation 14, 8 remaining
[2021-11-02 09:29:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:18] Number of windows considered: 1...
[2021-11-02 09:29:18] Bias-correcting 1 members separately...
[2021-11-02 09:29:18] Done.
Validation 15, 7 remaining
[2021-11-02 09:29:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:19] Number of windows considered: 1...
[2021-11-02 09:29:19] Bias-correcting 1 members separately...
[2021-11-02 09:29:19] Done.
Validation 16, 6 remaining
[2021-11-02 09:29:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:19] Number of windows considered: 1...
[2021-11-02 09:29:19] Bias-correcting 1 members separately...
[2021-11-02 09:29:19] Done.
Validation 17, 5 remaining
[2021-11-02 09:29:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:20] Number of windows considered: 1...
[2021-11-02 09:29:20] Bias-correcting 1 members separately...
[2021-11-02 09:29:20] Done.
Validation 18, 4 remaining
[2021-11-02 09:29:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:21] Number of windows considered: 1...
[2021-11-02 09:29:21] Bias-correcting 1 members separately...
[2021-11-02 09:29:21] Done.
Validation 19, 3 remaining
[2021-11-02 09:29:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:22] Number of windows considered: 1...
[2021-11-02 09:29:22] Bias-correcting 1 members separately...
[2021-11-02 09:29:22] Done.
Validation 20, 2 remaining
[2021-11-02 09:29:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:22] Number of windows considered: 1...
[2021-11-02 09:29:22] Bias-correcting 1 members separately...
[2021-11-02 09:29:22] Done.
Validation 21, 1 remaining
[2021-11-02 09:29:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:23] Number of windows considered: 1...
[2021-11-02 09:29:23] Bias-correcting 1 members separately...
[2021-11-02 09:29:23] Done.
Validation 22, 0 remaining
[2021-11-02 09:29:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:24] Number of windows considered: 1...
[2021-11-02 09:29:24] Bias-correcting 1 members separately...
[2021-11-02 09:29:24] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl4.gpqm2$Dates$start <- as.POSIXct(cal.station.cl4.gpqm2$Dates$start,tz = "GMT")
cal.station.cl4.gpqm2$Dates$end <- as.POSIXct(cal.station.cl4.gpqm2$Dates$end,tz = "GMT")
cal.station.cl5.pqm <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:29:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:25] Number of windows considered: 1...
[2021-11-02 09:29:25] Bias-correcting 1 members separately...
[2021-11-02 09:29:25] Done.
Validation 2, 20 remaining
[2021-11-02 09:29:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:25] Number of windows considered: 1...
[2021-11-02 09:29:25] Bias-correcting 1 members separately...
[2021-11-02 09:29:25] Done.
Validation 3, 19 remaining
[2021-11-02 09:29:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:26] Number of windows considered: 1...
[2021-11-02 09:29:26] Bias-correcting 1 members separately...
[2021-11-02 09:29:26] Done.
Validation 4, 18 remaining
[2021-11-02 09:29:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:27] Number of windows considered: 1...
[2021-11-02 09:29:27] Bias-correcting 1 members separately...
[2021-11-02 09:29:27] Done.
Validation 5, 17 remaining
[2021-11-02 09:29:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:27] Number of windows considered: 1...
[2021-11-02 09:29:27] Bias-correcting 1 members separately...
[2021-11-02 09:29:27] Done.
Validation 6, 16 remaining
[2021-11-02 09:29:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:28] Number of windows considered: 1...
[2021-11-02 09:29:28] Bias-correcting 1 members separately...
[2021-11-02 09:29:28] Done.
Validation 7, 15 remaining
[2021-11-02 09:29:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:29] Number of windows considered: 1...
[2021-11-02 09:29:29] Bias-correcting 1 members separately...
[2021-11-02 09:29:29] Done.
Validation 8, 14 remaining
[2021-11-02 09:29:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:29] Number of windows considered: 1...
[2021-11-02 09:29:29] Bias-correcting 1 members separately...
[2021-11-02 09:29:29] Done.
Validation 9, 13 remaining
[2021-11-02 09:29:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:30] Number of windows considered: 1...
[2021-11-02 09:29:30] Bias-correcting 1 members separately...
[2021-11-02 09:29:30] Done.
Validation 10, 12 remaining
[2021-11-02 09:29:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:31] Number of windows considered: 1...
[2021-11-02 09:29:31] Bias-correcting 1 members separately...
[2021-11-02 09:29:31] Done.
Validation 11, 11 remaining
[2021-11-02 09:29:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:31] Number of windows considered: 1...
[2021-11-02 09:29:31] Bias-correcting 1 members separately...
[2021-11-02 09:29:31] Done.
Validation 12, 10 remaining
[2021-11-02 09:29:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:32] Number of windows considered: 1...
[2021-11-02 09:29:32] Bias-correcting 1 members separately...
[2021-11-02 09:29:32] Done.
Validation 13, 9 remaining
[2021-11-02 09:29:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:33] Number of windows considered: 1...
[2021-11-02 09:29:33] Bias-correcting 1 members separately...
[2021-11-02 09:29:33] Done.
Validation 14, 8 remaining
[2021-11-02 09:29:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:33] Number of windows considered: 1...
[2021-11-02 09:29:33] Bias-correcting 1 members separately...
[2021-11-02 09:29:33] Done.
Validation 15, 7 remaining
[2021-11-02 09:29:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:34] Number of windows considered: 1...
[2021-11-02 09:29:34] Bias-correcting 1 members separately...
[2021-11-02 09:29:34] Done.
Validation 16, 6 remaining
[2021-11-02 09:29:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:35] Number of windows considered: 1...
[2021-11-02 09:29:35] Bias-correcting 1 members separately...
[2021-11-02 09:29:35] Done.
Validation 17, 5 remaining
[2021-11-02 09:29:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:35] Number of windows considered: 1...
[2021-11-02 09:29:35] Bias-correcting 1 members separately...
[2021-11-02 09:29:35] Done.
Validation 18, 4 remaining
[2021-11-02 09:29:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:36] Number of windows considered: 1...
[2021-11-02 09:29:36] Bias-correcting 1 members separately...
[2021-11-02 09:29:36] Done.
Validation 19, 3 remaining
[2021-11-02 09:29:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:37] Number of windows considered: 1...
[2021-11-02 09:29:37] Bias-correcting 1 members separately...
[2021-11-02 09:29:37] Done.
Validation 20, 2 remaining
[2021-11-02 09:29:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:38] Number of windows considered: 1...
[2021-11-02 09:29:38] Bias-correcting 1 members separately...
[2021-11-02 09:29:38] Done.
Validation 21, 1 remaining
[2021-11-02 09:29:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:38] Number of windows considered: 1...
[2021-11-02 09:29:38] Bias-correcting 1 members separately...
[2021-11-02 09:29:38] Done.
Validation 22, 0 remaining
[2021-11-02 09:29:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:39] Number of windows considered: 1...
[2021-11-02 09:29:39] Bias-correcting 1 members separately...
[2021-11-02 09:29:39] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl5.pqm$Dates$start <- as.POSIXct(cal.station.cl5.pqm$Dates$start,tz = "GMT")
cal.station.cl5.pqm$Dates$end <- as.POSIXct(cal.station.cl5.pqm$Dates$end,tz = "GMT")
idx <- which(!is.na(cal.station.cl1.pqm$Data))
cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl2.pqm$Data))
cal.station.cl2.pqm <- subsetDimension(cal.station.cl2.pqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl3.pqm$Data))
cal.station.cl3.pqm <- subsetDimension(cal.station.cl3.pqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl4.gpqm2$Data))
cal.station.cl4.gpqm2 <- subsetDimension(cal.station.cl4.gpqm2, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl5.pqm$Data))
cal.station.cl5.pqm <- subsetDimension(cal.station.cl5.pqm, dimension = "time", indices = idx)
wt_conditioned <- bindGrid(cal.station.cl1.pqm, cal.station.cl2.pqm, cal.station.cl3.pqm,
cal.station.cl4.gpqm2, cal.station.cl5.pqm, dimension = "time")
attr(wt_conditioned$Data, "dimensions") <- "time"
#cambiar de tipo de biasCorrection y fillGridDates
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "eqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-11-02 09:29:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:58] Number of windows considered: 1...
[2021-11-02 09:29:58] Bias-correcting 1 members separately...
[2021-11-02 09:29:58] Done.
Validation 2, 20 remaining
[2021-11-02 09:29:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:58] Number of windows considered: 1...
[2021-11-02 09:29:58] Bias-correcting 1 members separately...
[2021-11-02 09:29:59] Done.
Validation 3, 19 remaining
[2021-11-02 09:29:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:29:59] Number of windows considered: 1...
[2021-11-02 09:29:59] Bias-correcting 1 members separately...
[2021-11-02 09:29:59] Done.
Validation 4, 18 remaining
[2021-11-02 09:30:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:00] Number of windows considered: 1...
[2021-11-02 09:30:00] Bias-correcting 1 members separately...
[2021-11-02 09:30:00] Done.
Validation 5, 17 remaining
[2021-11-02 09:30:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:01] Number of windows considered: 1...
[2021-11-02 09:30:01] Bias-correcting 1 members separately...
[2021-11-02 09:30:01] Done.
Validation 6, 16 remaining
[2021-11-02 09:30:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:02] Number of windows considered: 1...
[2021-11-02 09:30:02] Bias-correcting 1 members separately...
[2021-11-02 09:30:02] Done.
Validation 7, 15 remaining
[2021-11-02 09:30:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:03] Number of windows considered: 1...
[2021-11-02 09:30:03] Bias-correcting 1 members separately...
[2021-11-02 09:30:03] Done.
Validation 8, 14 remaining
[2021-11-02 09:30:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:03] Number of windows considered: 1...
[2021-11-02 09:30:03] Bias-correcting 1 members separately...
[2021-11-02 09:30:03] Done.
Validation 9, 13 remaining
[2021-11-02 09:30:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:04] Number of windows considered: 1...
[2021-11-02 09:30:04] Bias-correcting 1 members separately...
[2021-11-02 09:30:04] Done.
Validation 10, 12 remaining
[2021-11-02 09:30:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:05] Number of windows considered: 1...
[2021-11-02 09:30:05] Bias-correcting 1 members separately...
[2021-11-02 09:30:05] Done.
Validation 11, 11 remaining
[2021-11-02 09:30:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:06] Number of windows considered: 1...
[2021-11-02 09:30:06] Bias-correcting 1 members separately...
[2021-11-02 09:30:06] Done.
Validation 12, 10 remaining
[2021-11-02 09:30:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:07] Number of windows considered: 1...
[2021-11-02 09:30:07] Bias-correcting 1 members separately...
[2021-11-02 09:30:07] Done.
Validation 13, 9 remaining
[2021-11-02 09:30:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:08] Number of windows considered: 1...
[2021-11-02 09:30:08] Bias-correcting 1 members separately...
[2021-11-02 09:30:08] Done.
Validation 14, 8 remaining
[2021-11-02 09:30:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:08] Number of windows considered: 1...
[2021-11-02 09:30:08] Bias-correcting 1 members separately...
[2021-11-02 09:30:08] Done.
Validation 15, 7 remaining
[2021-11-02 09:30:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:09] Number of windows considered: 1...
[2021-11-02 09:30:09] Bias-correcting 1 members separately...
[2021-11-02 09:30:09] Done.
Validation 16, 6 remaining
[2021-11-02 09:30:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:10] Number of windows considered: 1...
[2021-11-02 09:30:10] Bias-correcting 1 members separately...
[2021-11-02 09:30:10] Done.
Validation 17, 5 remaining
[2021-11-02 09:30:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:11] Number of windows considered: 1...
[2021-11-02 09:30:11] Bias-correcting 1 members separately...
[2021-11-02 09:30:11] Done.
Validation 18, 4 remaining
[2021-11-02 09:30:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:12] Number of windows considered: 1...
[2021-11-02 09:30:12] Bias-correcting 1 members separately...
[2021-11-02 09:30:12] Done.
Validation 19, 3 remaining
[2021-11-02 09:30:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:13] Number of windows considered: 1...
[2021-11-02 09:30:13] Bias-correcting 1 members separately...
[2021-11-02 09:30:13] Done.
Validation 20, 2 remaining
[2021-11-02 09:30:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:14] Number of windows considered: 1...
[2021-11-02 09:30:14] Bias-correcting 1 members separately...
[2021-11-02 09:30:14] Done.
Validation 21, 1 remaining
[2021-11-02 09:30:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:15] Number of windows considered: 1...
[2021-11-02 09:30:15] Bias-correcting 1 members separately...
[2021-11-02 09:30:15] Done.
Validation 22, 0 remaining
[2021-11-02 09:30:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:30:16] Number of windows considered: 1...
[2021-11-02 09:30:16] Bias-correcting 1 members separately...
[2021-11-02 09:30:16] Done.
# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))
index.combinated.rv20max <- MaxReturnValue(wt_conditioned)
[2021-11-02 09:30:23] Performing annual aggregation...
[2021-11-02 09:30:23] Done.
[2021-11-02 09:30:23] - Computing climatology...
[2021-11-02 09:30:23] - Done.
index.combinated <- c(index.combinated, index.combinated.rv20max)
index.eqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.eqm <- c(index.eqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.eqm.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 09:30:26] Performing annual aggregation...
[2021-11-02 09:30:26] Done.
[2021-11-02 09:30:26] - Computing climatology...
[2021-11-02 09:30:26] - Done.
index.eqm<- c(index.eqm ,index.eqm.rv20max)
index.eqm
Skewness SDII R10 R10p R20 R20p P98Wet
5.025837e+00 2.031420e+01 2.928803e-01 8.185069e+04 1.740105e-01 6.797294e+04 9.992785e+01
P98WetAmount RV20_max
1.317090e+04 3.847126e+02
diff.conditioned <- abs(index.obs-index.combinated)
diff.eqm <- abs(index.obs-index.eqm)
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
score.combinated <- c()
for (i in c(1:9)) {
score.combinated <- c(score.combinated, norm.vector[[i]][5])
}
score.combinated <- mean(score.combinated)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
Combined EQM-C PQM-C GPQM2-C GPQM-C
0.7799137 0.5892721 0.4859136 0.4742867 0.2763350
df <- data.frame(index.obs, index.combinated, index.eqm)
colnames(df) <- c("Observation","Conditioned", "EQM")
format(df, digits = 3, scientific = 5)
bias.df <- data.frame(diff.conditioned, diff.eqm)
colnames(bias.df) <- c("Bias Conditioned", "Bias EQM")
format(bias.df, digits = 3, scientific = 5)
df.st1 <- df
bias.df.st1 <- bias.df
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100
names(bias.rel.cond) <- names(diff.conditioned)
bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100
names(bias.rel.no.cond) <- names(diff.conditioned)
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)
colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias EQM")
format(bias.rel.df, digits = 3, scientific = 5)
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))
abline(a = 0, b = 1)
station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))
points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))
idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))
station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)
points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)
legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))
grid()

Alofi, Niue
i=2
station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
[2021-10-29 16:36:16] Performing annual aggregation...
[2021-10-29 16:36:16] Done.
[2021-10-29 16:36:16] - Computing climatology...
[2021-10-29 16:36:16] - Done.
index.obs <- c(index.obs, index.obs.rv20max)
index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
[2021-10-29 16:36:16] Performing annual aggregation...
[2021-10-29 16:36:16] Done.
[2021-10-29 16:36:16] - Computing climatology...
[2021-10-29 16:36:16] - Done.
index.trmm <- c(index.trmm, index.trmm.rv20max)
WT1
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))
station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
[2021-10-29 16:36:16] Performing annual aggregation...
[2021-10-29 16:36:16] Done.
[2021-10-29 16:36:16] - Computing climatology...
[2021-10-29 16:36:16] - Done.
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)
index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
[2021-10-29 16:36:17] Performing annual aggregation...
[2021-10-29 16:36:17] Done.
[2021-10-29 16:36:17] - Computing climatology...
[2021-10-29 16:36:17] - Done.
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")
station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "pqm",cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:36:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:18] Number of windows considered: 1...
[2021-10-29 16:36:18] Bias-correcting 1 members separately...
[2021-10-29 16:36:18] Done.
Validation 2, 20 remaining
[2021-10-29 16:36:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:19] Number of windows considered: 1...
[2021-10-29 16:36:19] Bias-correcting 1 members separately...
[2021-10-29 16:36:19] Done.
Validation 3, 19 remaining
[2021-10-29 16:36:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:22] Number of windows considered: 1...
[2021-10-29 16:36:22] Bias-correcting 1 members separately...
[2021-10-29 16:36:22] Done.
Validation 4, 18 remaining
[2021-10-29 16:36:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:24] Number of windows considered: 1...
[2021-10-29 16:36:24] Bias-correcting 1 members separately...
[2021-10-29 16:36:24] Done.
Validation 5, 17 remaining
[2021-10-29 16:36:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:25] Number of windows considered: 1...
[2021-10-29 16:36:25] Bias-correcting 1 members separately...
[2021-10-29 16:36:25] Done.
Validation 6, 16 remaining
[2021-10-29 16:36:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:27] Number of windows considered: 1...
[2021-10-29 16:36:27] Bias-correcting 1 members separately...
[2021-10-29 16:36:27] Done.
Validation 7, 15 remaining
[2021-10-29 16:36:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:28] Number of windows considered: 1...
[2021-10-29 16:36:28] Bias-correcting 1 members separately...
[2021-10-29 16:36:28] Done.
Validation 8, 14 remaining
[2021-10-29 16:36:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:30] Number of windows considered: 1...
[2021-10-29 16:36:30] Bias-correcting 1 members separately...
[2021-10-29 16:36:30] Done.
Validation 9, 13 remaining
[2021-10-29 16:36:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:32] Number of windows considered: 1...
[2021-10-29 16:36:32] Bias-correcting 1 members separately...
[2021-10-29 16:36:32] Done.
Validation 10, 12 remaining
[2021-10-29 16:36:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:33] Number of windows considered: 1...
[2021-10-29 16:36:33] Bias-correcting 1 members separately...
[2021-10-29 16:36:33] Done.
Validation 11, 11 remaining
[2021-10-29 16:36:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:35] Number of windows considered: 1...
[2021-10-29 16:36:35] Bias-correcting 1 members separately...
[2021-10-29 16:36:35] Done.
Validation 12, 10 remaining
[2021-10-29 16:36:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:36] Number of windows considered: 1...
[2021-10-29 16:36:36] Bias-correcting 1 members separately...
[2021-10-29 16:36:36] Done.
Validation 13, 9 remaining
[2021-10-29 16:36:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:38] Number of windows considered: 1...
[2021-10-29 16:36:38] Bias-correcting 1 members separately...
[2021-10-29 16:36:38] Done.
Validation 14, 8 remaining
[2021-10-29 16:36:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:40] Number of windows considered: 1...
[2021-10-29 16:36:40] Bias-correcting 1 members separately...
[2021-10-29 16:36:40] Done.
Validation 15, 7 remaining
[2021-10-29 16:36:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:41] Number of windows considered: 1...
[2021-10-29 16:36:41] Bias-correcting 1 members separately...
[2021-10-29 16:36:42] Done.
Validation 16, 6 remaining
[2021-10-29 16:36:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:43] Number of windows considered: 1...
[2021-10-29 16:36:43] Bias-correcting 1 members separately...
[2021-10-29 16:36:43] Done.
Validation 17, 5 remaining
[2021-10-29 16:36:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:45] Number of windows considered: 1...
[2021-10-29 16:36:45] Bias-correcting 1 members separately...
[2021-10-29 16:36:45] Done.
Validation 18, 4 remaining
[2021-10-29 16:36:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:46] Number of windows considered: 1...
[2021-10-29 16:36:46] Bias-correcting 1 members separately...
[2021-10-29 16:36:46] Done.
Validation 19, 3 remaining
[2021-10-29 16:36:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:48] Number of windows considered: 1...
[2021-10-29 16:36:48] Bias-correcting 1 members separately...
[2021-10-29 16:36:48] Done.
Validation 20, 2 remaining
[2021-10-29 16:36:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:50] Number of windows considered: 1...
[2021-10-29 16:36:50] Bias-correcting 1 members separately...
[2021-10-29 16:36:50] Done.
Validation 21, 1 remaining
[2021-10-29 16:36:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:52] Number of windows considered: 1...
[2021-10-29 16:36:52] Bias-correcting 1 members separately...
[2021-10-29 16:36:52] Done.
Validation 22, 0 remaining
[2021-10-29 16:36:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:53] Number of windows considered: 1...
[2021-10-29 16:36:53] Bias-correcting 1 members separately...
[2021-10-29 16:36:53] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 16:36:55] Performing annual aggregation...
[2021-10-29 16:36:55] Done.
[2021-10-29 16:36:55] - Computing climatology...
[2021-10-29 16:36:55] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.pqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:36:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:56] Number of windows considered: 1...
[2021-10-29 16:36:56] Bias-correcting 1 members separately...
[2021-10-29 16:36:57] Done.
Validation 2, 20 remaining
[2021-10-29 16:36:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:36:58] Number of windows considered: 1...
[2021-10-29 16:36:58] Bias-correcting 1 members separately...
[2021-10-29 16:36:59] Done.
Validation 3, 19 remaining
[2021-10-29 16:37:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:00] Number of windows considered: 1...
[2021-10-29 16:37:00] Bias-correcting 1 members separately...
[2021-10-29 16:37:00] Done.
Validation 4, 18 remaining
[2021-10-29 16:37:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:02] Number of windows considered: 1...
[2021-10-29 16:37:02] Bias-correcting 1 members separately...
[2021-10-29 16:37:02] Done.
Validation 5, 17 remaining
[2021-10-29 16:37:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:04] Number of windows considered: 1...
[2021-10-29 16:37:04] Bias-correcting 1 members separately...
[2021-10-29 16:37:04] Done.
Validation 6, 16 remaining
[2021-10-29 16:37:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:06] Number of windows considered: 1...
[2021-10-29 16:37:06] Bias-correcting 1 members separately...
[2021-10-29 16:37:06] Done.
Validation 7, 15 remaining
[2021-10-29 16:37:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:08] Number of windows considered: 1...
[2021-10-29 16:37:08] Bias-correcting 1 members separately...
[2021-10-29 16:37:08] Done.
Validation 8, 14 remaining
[2021-10-29 16:37:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:10] Number of windows considered: 1...
[2021-10-29 16:37:10] Bias-correcting 1 members separately...
[2021-10-29 16:37:10] Done.
Validation 9, 13 remaining
[2021-10-29 16:37:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:12] Number of windows considered: 1...
[2021-10-29 16:37:12] Bias-correcting 1 members separately...
[2021-10-29 16:37:12] Done.
Validation 10, 12 remaining
[2021-10-29 16:37:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:14] Number of windows considered: 1...
[2021-10-29 16:37:14] Bias-correcting 1 members separately...
[2021-10-29 16:37:14] Done.
Validation 11, 11 remaining
[2021-10-29 16:37:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:16] Number of windows considered: 1...
[2021-10-29 16:37:16] Bias-correcting 1 members separately...
[2021-10-29 16:37:16] Done.
Validation 12, 10 remaining
[2021-10-29 16:37:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:18] Number of windows considered: 1...
[2021-10-29 16:37:18] Bias-correcting 1 members separately...
[2021-10-29 16:37:18] Done.
Validation 13, 9 remaining
[2021-10-29 16:37:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:19] Number of windows considered: 1...
[2021-10-29 16:37:19] Bias-correcting 1 members separately...
[2021-10-29 16:37:20] Done.
Validation 14, 8 remaining
[2021-10-29 16:37:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:21] Number of windows considered: 1...
[2021-10-29 16:37:21] Bias-correcting 1 members separately...
[2021-10-29 16:37:22] Done.
Validation 15, 7 remaining
[2021-10-29 16:37:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:23] Number of windows considered: 1...
[2021-10-29 16:37:23] Bias-correcting 1 members separately...
[2021-10-29 16:37:23] Done.
Validation 16, 6 remaining
[2021-10-29 16:37:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:25] Number of windows considered: 1...
[2021-10-29 16:37:25] Bias-correcting 1 members separately...
[2021-10-29 16:37:25] Done.
Validation 17, 5 remaining
[2021-10-29 16:37:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:27] Number of windows considered: 1...
[2021-10-29 16:37:27] Bias-correcting 1 members separately...
[2021-10-29 16:37:27] Done.
Validation 18, 4 remaining
[2021-10-29 16:37:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:29] Number of windows considered: 1...
[2021-10-29 16:37:29] Bias-correcting 1 members separately...
[2021-10-29 16:37:29] Done.
Validation 19, 3 remaining
[2021-10-29 16:37:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:31] Number of windows considered: 1...
[2021-10-29 16:37:31] Bias-correcting 1 members separately...
[2021-10-29 16:37:31] Done.
Validation 20, 2 remaining
[2021-10-29 16:37:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:32] Number of windows considered: 1...
[2021-10-29 16:37:32] Bias-correcting 1 members separately...
[2021-10-29 16:37:33] Done.
Validation 21, 1 remaining
[2021-10-29 16:37:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:34] Number of windows considered: 1...
[2021-10-29 16:37:34] Bias-correcting 1 members separately...
[2021-10-29 16:37:35] Done.
Validation 22, 0 remaining
[2021-10-29 16:37:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:36] Number of windows considered: 1...
[2021-10-29 16:37:36] Bias-correcting 1 members separately...
[2021-10-29 16:37:36] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 16:37:38] Performing annual aggregation...
[2021-10-29 16:37:38] Done.
[2021-10-29 16:37:38] - Computing climatology...
[2021-10-29 16:37:38] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.eqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:37:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:40] Number of windows considered: 1...
[2021-10-29 16:37:40] Bias-correcting 1 members separately...
[2021-10-29 16:37:40] Done.
Validation 2, 20 remaining
[2021-10-29 16:37:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:42] Number of windows considered: 1...
[2021-10-29 16:37:42] Bias-correcting 1 members separately...
[2021-10-29 16:37:42] Done.
Validation 3, 19 remaining
[2021-10-29 16:37:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:43] Number of windows considered: 1...
[2021-10-29 16:37:43] Bias-correcting 1 members separately...
[2021-10-29 16:37:44] Done.
Validation 4, 18 remaining
[2021-10-29 16:37:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:45] Number of windows considered: 1...
[2021-10-29 16:37:45] Bias-correcting 1 members separately...
[2021-10-29 16:37:45] Done.
Validation 5, 17 remaining
[2021-10-29 16:37:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:47] Number of windows considered: 1...
[2021-10-29 16:37:47] Bias-correcting 1 members separately...
[2021-10-29 16:37:47] Done.
Validation 6, 16 remaining
[2021-10-29 16:37:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:49] Number of windows considered: 1...
[2021-10-29 16:37:49] Bias-correcting 1 members separately...
[2021-10-29 16:37:49] Done.
Validation 7, 15 remaining
[2021-10-29 16:37:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:51] Number of windows considered: 1...
[2021-10-29 16:37:51] Bias-correcting 1 members separately...
[2021-10-29 16:37:51] Done.
Validation 8, 14 remaining
[2021-10-29 16:37:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:53] Number of windows considered: 1...
[2021-10-29 16:37:53] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:37:53] Done.
Validation 9, 13 remaining
[2021-10-29 16:37:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:55] Number of windows considered: 1...
[2021-10-29 16:37:55] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:37:55] Done.
Validation 10, 12 remaining
[2021-10-29 16:37:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:56] Number of windows considered: 1...
[2021-10-29 16:37:56] Bias-correcting 1 members separately...
[2021-10-29 16:37:57] Done.
Validation 11, 11 remaining
[2021-10-29 16:37:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:37:58] Number of windows considered: 1...
[2021-10-29 16:37:58] Bias-correcting 1 members separately...
[2021-10-29 16:37:59] Done.
Validation 12, 10 remaining
[2021-10-29 16:38:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:00] Number of windows considered: 1...
[2021-10-29 16:38:00] Bias-correcting 1 members separately...
[2021-10-29 16:38:01] Done.
Validation 13, 9 remaining
[2021-10-29 16:38:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:02] Number of windows considered: 1...
[2021-10-29 16:38:02] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:38:02] Done.
Validation 14, 8 remaining
[2021-10-29 16:38:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:04] Number of windows considered: 1...
[2021-10-29 16:38:04] Bias-correcting 1 members separately...
[2021-10-29 16:38:05] Done.
Validation 15, 7 remaining
[2021-10-29 16:38:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:06] Number of windows considered: 1...
[2021-10-29 16:38:06] Bias-correcting 1 members separately...
[2021-10-29 16:38:06] Done.
Validation 16, 6 remaining
[2021-10-29 16:38:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:08] Number of windows considered: 1...
[2021-10-29 16:38:08] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:38:08] Done.
Validation 17, 5 remaining
[2021-10-29 16:38:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:09] Number of windows considered: 1...
[2021-10-29 16:38:09] Bias-correcting 1 members separately...
[2021-10-29 16:38:09] Done.
Validation 18, 4 remaining
[2021-10-29 16:38:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:11] Number of windows considered: 1...
[2021-10-29 16:38:11] Bias-correcting 1 members separately...
[2021-10-29 16:38:11] Done.
Validation 19, 3 remaining
[2021-10-29 16:38:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:12] Number of windows considered: 1...
[2021-10-29 16:38:12] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:38:12] Done.
Validation 20, 2 remaining
[2021-10-29 16:38:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:14] Number of windows considered: 1...
[2021-10-29 16:38:14] Bias-correcting 1 members separately...
[2021-10-29 16:38:14] Done.
Validation 21, 1 remaining
[2021-10-29 16:38:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:15] Number of windows considered: 1...
[2021-10-29 16:38:15] Bias-correcting 1 members separately...
[2021-10-29 16:38:15] Done.
Validation 22, 0 remaining
[2021-10-29 16:38:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:17] Number of windows considered: 1...
[2021-10-29 16:38:17] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:38:17] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 16:38:18] Performing annual aggregation...
[2021-10-29 16:38:18] Done.
[2021-10-29 16:38:18] - Computing climatology...
[2021-10-29 16:38:18] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:38:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:20] Number of windows considered: 1...
[2021-10-29 16:38:20] Bias-correcting 1 members separately...
[2021-10-29 16:38:20] Done.
Validation 2, 20 remaining
[2021-10-29 16:38:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:21] Number of windows considered: 1...
[2021-10-29 16:38:21] Bias-correcting 1 members separately...
[2021-10-29 16:38:22] Done.
Validation 3, 19 remaining
[2021-10-29 16:38:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:23] Number of windows considered: 1...
[2021-10-29 16:38:23] Bias-correcting 1 members separately...
[2021-10-29 16:38:23] Done.
Validation 4, 18 remaining
[2021-10-29 16:38:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:24] Number of windows considered: 1...
[2021-10-29 16:38:24] Bias-correcting 1 members separately...
[2021-10-29 16:38:25] Done.
Validation 5, 17 remaining
[2021-10-29 16:38:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:26] Number of windows considered: 1...
[2021-10-29 16:38:26] Bias-correcting 1 members separately...
[2021-10-29 16:38:26] Done.
Validation 6, 16 remaining
[2021-10-29 16:38:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:28] Number of windows considered: 1...
[2021-10-29 16:38:28] Bias-correcting 1 members separately...
[2021-10-29 16:38:28] Done.
Validation 7, 15 remaining
[2021-10-29 16:38:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:29] Number of windows considered: 1...
[2021-10-29 16:38:29] Bias-correcting 1 members separately...
[2021-10-29 16:38:29] Done.
Validation 8, 14 remaining
[2021-10-29 16:38:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:31] Number of windows considered: 1...
[2021-10-29 16:38:31] Bias-correcting 1 members separately...
[2021-10-29 16:38:31] Done.
Validation 9, 13 remaining
[2021-10-29 16:38:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:33] Number of windows considered: 1...
[2021-10-29 16:38:33] Bias-correcting 1 members separately...
[2021-10-29 16:38:33] Done.
Validation 10, 12 remaining
[2021-10-29 16:38:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:34] Number of windows considered: 1...
[2021-10-29 16:38:34] Bias-correcting 1 members separately...
[2021-10-29 16:38:34] Done.
Validation 11, 11 remaining
[2021-10-29 16:38:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:36] Number of windows considered: 1...
[2021-10-29 16:38:36] Bias-correcting 1 members separately...
[2021-10-29 16:38:36] Done.
Validation 12, 10 remaining
[2021-10-29 16:38:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:37] Number of windows considered: 1...
[2021-10-29 16:38:37] Bias-correcting 1 members separately...
[2021-10-29 16:38:37] Done.
Validation 13, 9 remaining
[2021-10-29 16:38:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:39] Number of windows considered: 1...
[2021-10-29 16:38:39] Bias-correcting 1 members separately...
[2021-10-29 16:38:39] Done.
Validation 14, 8 remaining
[2021-10-29 16:38:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:41] Number of windows considered: 1...
[2021-10-29 16:38:41] Bias-correcting 1 members separately...
[2021-10-29 16:38:41] Done.
Validation 15, 7 remaining
[2021-10-29 16:38:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:43] Number of windows considered: 1...
[2021-10-29 16:38:43] Bias-correcting 1 members separately...
[2021-10-29 16:38:44] Done.
Validation 16, 6 remaining
[2021-10-29 16:38:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:45] Number of windows considered: 1...
[2021-10-29 16:38:45] Bias-correcting 1 members separately...
[2021-10-29 16:38:45] Done.
Validation 17, 5 remaining
[2021-10-29 16:38:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:46] Number of windows considered: 1...
[2021-10-29 16:38:46] Bias-correcting 1 members separately...
[2021-10-29 16:38:46] Done.
Validation 18, 4 remaining
[2021-10-29 16:38:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:47] Number of windows considered: 1...
[2021-10-29 16:38:47] Bias-correcting 1 members separately...
[2021-10-29 16:38:47] Done.
Validation 19, 3 remaining
[2021-10-29 16:38:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:49] Number of windows considered: 1...
[2021-10-29 16:38:49] Bias-correcting 1 members separately...
[2021-10-29 16:38:49] Done.
Validation 20, 2 remaining
[2021-10-29 16:38:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:50] Number of windows considered: 1...
[2021-10-29 16:38:50] Bias-correcting 1 members separately...
[2021-10-29 16:38:50] Done.
Validation 21, 1 remaining
[2021-10-29 16:38:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:51] Number of windows considered: 1...
[2021-10-29 16:38:51] Bias-correcting 1 members separately...
[2021-10-29 16:38:51] Done.
Validation 22, 0 remaining
[2021-10-29 16:38:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:52] Number of windows considered: 1...
[2021-10-29 16:38:52] Bias-correcting 1 members separately...
[2021-10-29 16:38:52] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 16:38:53] Performing annual aggregation...
[2021-10-29 16:38:53] Done.
[2021-10-29 16:38:53] - Computing climatology...
[2021-10-29 16:38:53] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm2.cl1 <- index.cal.station.cl1
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i]))
}
normalization <- function(measure){
measure.norm <- c()
#measure must be a vector with the value of a certain measure of different calibrations
for (i in c(1:length(measure))) {
measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
}
return(measure.norm)
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
scores.st2.wt1 <- scores
WT2
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))
station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
[2021-10-29 16:38:54] Performing annual aggregation...
[2021-10-29 16:38:54] Done.
[2021-10-29 16:38:54] - Computing climatology...
[2021-10-29 16:38:54] - Done.
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)
index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
[2021-10-29 16:38:54] Performing annual aggregation...
[2021-10-29 16:38:54] Done.
[2021-10-29 16:38:54] - Computing climatology...
[2021-10-29 16:38:54] - Done.
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")
station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:38:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:56] Number of windows considered: 1...
[2021-10-29 16:38:56] Bias-correcting 1 members separately...
[2021-10-29 16:38:56] Done.
Validation 2, 20 remaining
[2021-10-29 16:38:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:57] Number of windows considered: 1...
[2021-10-29 16:38:57] Bias-correcting 1 members separately...
[2021-10-29 16:38:57] Done.
Validation 3, 19 remaining
[2021-10-29 16:38:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:58] Number of windows considered: 1...
[2021-10-29 16:38:58] Bias-correcting 1 members separately...
[2021-10-29 16:38:58] Done.
Validation 4, 18 remaining
[2021-10-29 16:38:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:38:59] Number of windows considered: 1...
[2021-10-29 16:38:59] Bias-correcting 1 members separately...
[2021-10-29 16:39:00] Done.
Validation 5, 17 remaining
[2021-10-29 16:39:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:01] Number of windows considered: 1...
[2021-10-29 16:39:01] Bias-correcting 1 members separately...
[2021-10-29 16:39:01] Done.
Validation 6, 16 remaining
[2021-10-29 16:39:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:03] Number of windows considered: 1...
[2021-10-29 16:39:03] Bias-correcting 1 members separately...
[2021-10-29 16:39:03] Done.
Validation 7, 15 remaining
[2021-10-29 16:39:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:04] Number of windows considered: 1...
[2021-10-29 16:39:04] Bias-correcting 1 members separately...
[2021-10-29 16:39:04] Done.
Validation 8, 14 remaining
[2021-10-29 16:39:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:06] Number of windows considered: 1...
[2021-10-29 16:39:06] Bias-correcting 1 members separately...
[2021-10-29 16:39:06] Done.
Validation 9, 13 remaining
[2021-10-29 16:39:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:07] Number of windows considered: 1...
[2021-10-29 16:39:07] Bias-correcting 1 members separately...
[2021-10-29 16:39:07] Done.
Validation 10, 12 remaining
[2021-10-29 16:39:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:09] Number of windows considered: 1...
[2021-10-29 16:39:09] Bias-correcting 1 members separately...
[2021-10-29 16:39:09] Done.
Validation 11, 11 remaining
[2021-10-29 16:39:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:10] Number of windows considered: 1...
[2021-10-29 16:39:10] Bias-correcting 1 members separately...
[2021-10-29 16:39:10] Done.
Validation 12, 10 remaining
[2021-10-29 16:39:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:12] Number of windows considered: 1...
[2021-10-29 16:39:12] Bias-correcting 1 members separately...
[2021-10-29 16:39:12] Done.
Validation 13, 9 remaining
[2021-10-29 16:39:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:14] Number of windows considered: 1...
[2021-10-29 16:39:14] Bias-correcting 1 members separately...
[2021-10-29 16:39:14] Done.
Validation 14, 8 remaining
[2021-10-29 16:39:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:15] Number of windows considered: 1...
[2021-10-29 16:39:15] Bias-correcting 1 members separately...
[2021-10-29 16:39:15] Done.
Validation 15, 7 remaining
[2021-10-29 16:39:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:17] Number of windows considered: 1...
[2021-10-29 16:39:17] Bias-correcting 1 members separately...
[2021-10-29 16:39:17] Done.
Validation 16, 6 remaining
[2021-10-29 16:39:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:19] Number of windows considered: 1...
[2021-10-29 16:39:19] Bias-correcting 1 members separately...
[2021-10-29 16:39:19] Done.
Validation 17, 5 remaining
[2021-10-29 16:39:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:20] Number of windows considered: 1...
[2021-10-29 16:39:20] Bias-correcting 1 members separately...
[2021-10-29 16:39:20] Done.
Validation 18, 4 remaining
[2021-10-29 16:39:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:21] Number of windows considered: 1...
[2021-10-29 16:39:21] Bias-correcting 1 members separately...
[2021-10-29 16:39:21] Done.
Validation 19, 3 remaining
[2021-10-29 16:39:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:22] Number of windows considered: 1...
[2021-10-29 16:39:22] Bias-correcting 1 members separately...
[2021-10-29 16:39:22] Done.
Validation 20, 2 remaining
[2021-10-29 16:39:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:23] Number of windows considered: 1...
[2021-10-29 16:39:23] Bias-correcting 1 members separately...
[2021-10-29 16:39:23] Done.
Validation 21, 1 remaining
[2021-10-29 16:39:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:24] Number of windows considered: 1...
[2021-10-29 16:39:24] Bias-correcting 1 members separately...
[2021-10-29 16:39:24] Done.
Validation 22, 0 remaining
[2021-10-29 16:39:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:26] Number of windows considered: 1...
[2021-10-29 16:39:26] Bias-correcting 1 members separately...
[2021-10-29 16:39:26] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 16:39:26] Performing annual aggregation...
[2021-10-29 16:39:26] Done.
[2021-10-29 16:39:26] - Computing climatology...
[2021-10-29 16:39:26] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.pqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:39:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:28] Number of windows considered: 1...
[2021-10-29 16:39:28] Bias-correcting 1 members separately...
[2021-10-29 16:39:28] Done.
Validation 2, 20 remaining
[2021-10-29 16:39:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:29] Number of windows considered: 1...
[2021-10-29 16:39:29] Bias-correcting 1 members separately...
[2021-10-29 16:39:29] Done.
Validation 3, 19 remaining
[2021-10-29 16:39:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:30] Number of windows considered: 1...
[2021-10-29 16:39:30] Bias-correcting 1 members separately...
[2021-10-29 16:39:30] Done.
Validation 4, 18 remaining
[2021-10-29 16:39:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:32] Number of windows considered: 1...
[2021-10-29 16:39:32] Bias-correcting 1 members separately...
[2021-10-29 16:39:32] Done.
Validation 5, 17 remaining
[2021-10-29 16:39:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:33] Number of windows considered: 1...
[2021-10-29 16:39:33] Bias-correcting 1 members separately...
[2021-10-29 16:39:33] Done.
Validation 6, 16 remaining
[2021-10-29 16:39:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:34] Number of windows considered: 1...
[2021-10-29 16:39:34] Bias-correcting 1 members separately...
[2021-10-29 16:39:34] Done.
Validation 7, 15 remaining
[2021-10-29 16:39:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:35] Number of windows considered: 1...
[2021-10-29 16:39:35] Bias-correcting 1 members separately...
[2021-10-29 16:39:35] Done.
Validation 8, 14 remaining
[2021-10-29 16:39:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:36] Number of windows considered: 1...
[2021-10-29 16:39:36] Bias-correcting 1 members separately...
[2021-10-29 16:39:37] Done.
Validation 9, 13 remaining
[2021-10-29 16:39:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:38] Number of windows considered: 1...
[2021-10-29 16:39:38] Bias-correcting 1 members separately...
[2021-10-29 16:39:38] Done.
Validation 10, 12 remaining
[2021-10-29 16:39:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:39] Number of windows considered: 1...
[2021-10-29 16:39:39] Bias-correcting 1 members separately...
[2021-10-29 16:39:39] Done.
Validation 11, 11 remaining
[2021-10-29 16:39:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:40] Number of windows considered: 1...
[2021-10-29 16:39:40] Bias-correcting 1 members separately...
[2021-10-29 16:39:40] Done.
Validation 12, 10 remaining
[2021-10-29 16:39:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:41] Number of windows considered: 1...
[2021-10-29 16:39:41] Bias-correcting 1 members separately...
[2021-10-29 16:39:41] Done.
Validation 13, 9 remaining
[2021-10-29 16:39:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:42] Number of windows considered: 1...
[2021-10-29 16:39:42] Bias-correcting 1 members separately...
[2021-10-29 16:39:43] Done.
Validation 14, 8 remaining
[2021-10-29 16:39:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:44] Number of windows considered: 1...
[2021-10-29 16:39:44] Bias-correcting 1 members separately...
[2021-10-29 16:39:44] Done.
Validation 15, 7 remaining
[2021-10-29 16:39:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:45] Number of windows considered: 1...
[2021-10-29 16:39:45] Bias-correcting 1 members separately...
[2021-10-29 16:39:45] Done.
Validation 16, 6 remaining
[2021-10-29 16:39:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:46] Number of windows considered: 1...
[2021-10-29 16:39:46] Bias-correcting 1 members separately...
[2021-10-29 16:39:46] Done.
Validation 17, 5 remaining
[2021-10-29 16:39:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:47] Number of windows considered: 1...
[2021-10-29 16:39:47] Bias-correcting 1 members separately...
[2021-10-29 16:39:47] Done.
Validation 18, 4 remaining
[2021-10-29 16:39:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:49] Number of windows considered: 1...
[2021-10-29 16:39:49] Bias-correcting 1 members separately...
[2021-10-29 16:39:49] Done.
Validation 19, 3 remaining
[2021-10-29 16:39:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:50] Number of windows considered: 1...
[2021-10-29 16:39:50] Bias-correcting 1 members separately...
[2021-10-29 16:39:50] Done.
Validation 20, 2 remaining
[2021-10-29 16:39:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:51] Number of windows considered: 1...
[2021-10-29 16:39:51] Bias-correcting 1 members separately...
[2021-10-29 16:39:51] Done.
Validation 21, 1 remaining
[2021-10-29 16:39:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:52] Number of windows considered: 1...
[2021-10-29 16:39:52] Bias-correcting 1 members separately...
[2021-10-29 16:39:52] Done.
Validation 22, 0 remaining
[2021-10-29 16:39:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:53] Number of windows considered: 1...
[2021-10-29 16:39:53] Bias-correcting 1 members separately...
[2021-10-29 16:39:53] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 16:39:54] Performing annual aggregation...
[2021-10-29 16:39:54] Done.
[2021-10-29 16:39:54] - Computing climatology...
[2021-10-29 16:39:54] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.eqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:39:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:55] Number of windows considered: 1...
[2021-10-29 16:39:55] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:39:55] Done.
Validation 2, 20 remaining
[2021-10-29 16:39:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:56] Number of windows considered: 1...
[2021-10-29 16:39:56] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:39:56] Done.
Validation 3, 19 remaining
[2021-10-29 16:39:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:57] Number of windows considered: 1...
[2021-10-29 16:39:57] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:39:57] Done.
Validation 4, 18 remaining
[2021-10-29 16:39:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:58] Number of windows considered: 1...
[2021-10-29 16:39:58] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:39:58] Done.
Validation 5, 17 remaining
[2021-10-29 16:39:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:39:59] Number of windows considered: 1...
[2021-10-29 16:39:59] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:39:59] Done.
Validation 6, 16 remaining
[2021-10-29 16:40:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:00] Number of windows considered: 1...
[2021-10-29 16:40:00] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:00] Done.
Validation 7, 15 remaining
[2021-10-29 16:40:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:01] Number of windows considered: 1...
[2021-10-29 16:40:01] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:40:01] Done.
Validation 8, 14 remaining
[2021-10-29 16:40:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:02] Number of windows considered: 1...
[2021-10-29 16:40:02] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:02] Done.
Validation 9, 13 remaining
[2021-10-29 16:40:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:03] Number of windows considered: 1...
[2021-10-29 16:40:03] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:03] Done.
Validation 10, 12 remaining
[2021-10-29 16:40:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:04] Number of windows considered: 1...
[2021-10-29 16:40:04] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:04] Done.
Validation 11, 11 remaining
[2021-10-29 16:40:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:05] Number of windows considered: 1...
[2021-10-29 16:40:05] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:05] Done.
Validation 12, 10 remaining
[2021-10-29 16:40:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:06] Number of windows considered: 1...
[2021-10-29 16:40:06] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:40:06] Done.
Validation 13, 9 remaining
[2021-10-29 16:40:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:07] Number of windows considered: 1...
[2021-10-29 16:40:07] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:07] Done.
Validation 14, 8 remaining
[2021-10-29 16:40:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:08] Number of windows considered: 1...
[2021-10-29 16:40:08] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:40:08] Done.
Validation 15, 7 remaining
[2021-10-29 16:40:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:09] Number of windows considered: 1...
[2021-10-29 16:40:09] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:10] Done.
Validation 16, 6 remaining
[2021-10-29 16:40:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:10] Number of windows considered: 1...
[2021-10-29 16:40:10] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:11] Done.
Validation 17, 5 remaining
[2021-10-29 16:40:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:12] Number of windows considered: 1...
[2021-10-29 16:40:12] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:12] Done.
Validation 18, 4 remaining
[2021-10-29 16:40:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:13] Number of windows considered: 1...
[2021-10-29 16:40:13] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:40:13] Done.
Validation 19, 3 remaining
[2021-10-29 16:40:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:14] Number of windows considered: 1...
[2021-10-29 16:40:14] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:40:14] Done.
Validation 20, 2 remaining
[2021-10-29 16:40:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:15] Number of windows considered: 1...
[2021-10-29 16:40:15] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:15] Done.
Validation 21, 1 remaining
[2021-10-29 16:40:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:16] Number of windows considered: 1...
[2021-10-29 16:40:16] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:40:16] Done.
Validation 22, 0 remaining
[2021-10-29 16:40:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:17] Number of windows considered: 1...
[2021-10-29 16:40:17] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:40:17] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 16:40:18] Performing annual aggregation...
[2021-10-29 16:40:18] Done.
[2021-10-29 16:40:18] - Computing climatology...
[2021-10-29 16:40:18] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:40:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:19] Number of windows considered: 1...
[2021-10-29 16:40:19] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:19] Done.
Validation 2, 20 remaining
[2021-10-29 16:40:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:20] Number of windows considered: 1...
[2021-10-29 16:40:20] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:20] Done.
Validation 3, 19 remaining
[2021-10-29 16:40:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:21] Number of windows considered: 1...
[2021-10-29 16:40:21] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:21] Done.
Validation 4, 18 remaining
[2021-10-29 16:40:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:22] Number of windows considered: 1...
[2021-10-29 16:40:22] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:22] Done.
Validation 5, 17 remaining
[2021-10-29 16:40:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:23] Number of windows considered: 1...
[2021-10-29 16:40:23] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:23] Done.
Validation 6, 16 remaining
[2021-10-29 16:40:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:25] Number of windows considered: 1...
[2021-10-29 16:40:25] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:25] Done.
Validation 7, 15 remaining
[2021-10-29 16:40:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:26] Number of windows considered: 1...
[2021-10-29 16:40:26] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:26] Done.
Validation 8, 14 remaining
[2021-10-29 16:40:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:27] Number of windows considered: 1...
[2021-10-29 16:40:27] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:27] Done.
Validation 9, 13 remaining
[2021-10-29 16:40:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:28] Number of windows considered: 1...
[2021-10-29 16:40:28] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:28] Done.
Validation 10, 12 remaining
[2021-10-29 16:40:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:29] Number of windows considered: 1...
[2021-10-29 16:40:29] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:29] Done.
Validation 11, 11 remaining
[2021-10-29 16:40:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:30] Number of windows considered: 1...
[2021-10-29 16:40:30] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:30] Done.
Validation 12, 10 remaining
[2021-10-29 16:40:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:31] Number of windows considered: 1...
[2021-10-29 16:40:31] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 16:40:31] Done.
Validation 13, 9 remaining
[2021-10-29 16:40:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:32] Number of windows considered: 1...
[2021-10-29 16:40:32] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:32] Done.
Validation 14, 8 remaining
[2021-10-29 16:40:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:33] Number of windows considered: 1...
[2021-10-29 16:40:33] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:33] Done.
Validation 15, 7 remaining
[2021-10-29 16:40:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:34] Number of windows considered: 1...
[2021-10-29 16:40:34] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:35] Done.
Validation 16, 6 remaining
[2021-10-29 16:40:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:36] Number of windows considered: 1...
[2021-10-29 16:40:36] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:36] Done.
Validation 17, 5 remaining
[2021-10-29 16:40:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:37] Number of windows considered: 1...
[2021-10-29 16:40:37] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:37] Done.
Validation 18, 4 remaining
[2021-10-29 16:40:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:38] Number of windows considered: 1...
[2021-10-29 16:40:38] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:38] Done.
Validation 19, 3 remaining
[2021-10-29 16:40:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:39] Number of windows considered: 1...
[2021-10-29 16:40:39] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:39] Done.
Validation 20, 2 remaining
[2021-10-29 16:40:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:40] Number of windows considered: 1...
[2021-10-29 16:40:40] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:40] Done.
Validation 21, 1 remaining
[2021-10-29 16:40:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:41] Number of windows considered: 1...
[2021-10-29 16:40:41] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:41] Done.
Validation 22, 0 remaining
[2021-10-29 16:40:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:43] Number of windows considered: 1...
[2021-10-29 16:40:43] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:40:43] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 16:40:43] Performing annual aggregation...
[2021-10-29 16:40:43] Done.
[2021-10-29 16:40:43] - Computing climatology...
[2021-10-29 16:40:43] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm2.cl2 <- index.cal.station.cl2
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores
EQM-WT2 GPQM2-WT2 PQM-WT2 GPQM-WT2
0.6742460 0.5263504 0.5055766 0.3550338
scores.st2.wt2 <- scores
WT3
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))
station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
[2021-10-29 16:40:44] Performing annual aggregation...
[2021-10-29 16:40:44] Done.
[2021-10-29 16:40:44] - Computing climatology...
[2021-10-29 16:40:44] - Done.
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)
index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
[2021-10-29 16:40:44] Performing annual aggregation...
[2021-10-29 16:40:44] Done.
[2021-10-29 16:40:44] - Computing climatology...
[2021-10-29 16:40:44] - Done.
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")
station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:40:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:46] Number of windows considered: 1...
[2021-10-29 16:40:46] Bias-correcting 1 members separately...
[2021-10-29 16:40:46] Done.
Validation 2, 20 remaining
[2021-10-29 16:40:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:47] Number of windows considered: 1...
[2021-10-29 16:40:47] Bias-correcting 1 members separately...
[2021-10-29 16:40:47] Done.
Validation 3, 19 remaining
[2021-10-29 16:40:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:48] Number of windows considered: 1...
[2021-10-29 16:40:48] Bias-correcting 1 members separately...
[2021-10-29 16:40:48] Done.
Validation 4, 18 remaining
[2021-10-29 16:40:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:49] Number of windows considered: 1...
[2021-10-29 16:40:49] Bias-correcting 1 members separately...
[2021-10-29 16:40:49] Done.
Validation 5, 17 remaining
[2021-10-29 16:40:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:50] Number of windows considered: 1...
[2021-10-29 16:40:50] Bias-correcting 1 members separately...
[2021-10-29 16:40:51] Done.
Validation 6, 16 remaining
[2021-10-29 16:40:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:52] Number of windows considered: 1...
[2021-10-29 16:40:52] Bias-correcting 1 members separately...
[2021-10-29 16:40:52] Done.
Validation 7, 15 remaining
[2021-10-29 16:40:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:53] Number of windows considered: 1...
[2021-10-29 16:40:53] Bias-correcting 1 members separately...
[2021-10-29 16:40:53] Done.
Validation 8, 14 remaining
[2021-10-29 16:40:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:54] Number of windows considered: 1...
[2021-10-29 16:40:54] Bias-correcting 1 members separately...
[2021-10-29 16:40:54] Done.
Validation 9, 13 remaining
[2021-10-29 16:40:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:55] Number of windows considered: 1...
[2021-10-29 16:40:55] Bias-correcting 1 members separately...
[2021-10-29 16:40:55] Done.
Validation 10, 12 remaining
[2021-10-29 16:40:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:56] Number of windows considered: 1...
[2021-10-29 16:40:56] Bias-correcting 1 members separately...
[2021-10-29 16:40:57] Done.
Validation 11, 11 remaining
[2021-10-29 16:40:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:58] Number of windows considered: 1...
[2021-10-29 16:40:58] Bias-correcting 1 members separately...
[2021-10-29 16:40:58] Done.
Validation 12, 10 remaining
[2021-10-29 16:40:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:40:59] Number of windows considered: 1...
[2021-10-29 16:40:59] Bias-correcting 1 members separately...
[2021-10-29 16:40:59] Done.
Validation 13, 9 remaining
[2021-10-29 16:41:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:00] Number of windows considered: 1...
[2021-10-29 16:41:00] Bias-correcting 1 members separately...
[2021-10-29 16:41:00] Done.
Validation 14, 8 remaining
[2021-10-29 16:41:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:01] Number of windows considered: 1...
[2021-10-29 16:41:01] Bias-correcting 1 members separately...
[2021-10-29 16:41:01] Done.
Validation 15, 7 remaining
[2021-10-29 16:41:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:03] Number of windows considered: 1...
[2021-10-29 16:41:03] Bias-correcting 1 members separately...
[2021-10-29 16:41:03] Done.
Validation 16, 6 remaining
[2021-10-29 16:41:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:04] Number of windows considered: 1...
[2021-10-29 16:41:04] Bias-correcting 1 members separately...
[2021-10-29 16:41:04] Done.
Validation 17, 5 remaining
[2021-10-29 16:41:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:05] Number of windows considered: 1...
[2021-10-29 16:41:05] Bias-correcting 1 members separately...
[2021-10-29 16:41:05] Done.
Validation 18, 4 remaining
[2021-10-29 16:41:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:07] Number of windows considered: 1...
[2021-10-29 16:41:07] Bias-correcting 1 members separately...
[2021-10-29 16:41:07] Done.
Validation 19, 3 remaining
[2021-10-29 16:41:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:08] Number of windows considered: 1...
[2021-10-29 16:41:08] Bias-correcting 1 members separately...
[2021-10-29 16:41:08] Done.
Validation 20, 2 remaining
[2021-10-29 16:41:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:09] Number of windows considered: 1...
[2021-10-29 16:41:09] Bias-correcting 1 members separately...
[2021-10-29 16:41:09] Done.
Validation 21, 1 remaining
[2021-10-29 16:41:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:11] Number of windows considered: 1...
[2021-10-29 16:41:11] Bias-correcting 1 members separately...
[2021-10-29 16:41:11] Done.
Validation 22, 0 remaining
[2021-10-29 16:41:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:12] Number of windows considered: 1...
[2021-10-29 16:41:12] Bias-correcting 1 members separately...
[2021-10-29 16:41:12] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 16:41:13] Performing annual aggregation...
[2021-10-29 16:41:13] Done.
[2021-10-29 16:41:13] - Computing climatology...
[2021-10-29 16:41:13] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.pqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:41:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:14] Number of windows considered: 1...
[2021-10-29 16:41:14] Bias-correcting 1 members separately...
[2021-10-29 16:41:14] Done.
Validation 2, 20 remaining
[2021-10-29 16:41:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:15] Number of windows considered: 1...
[2021-10-29 16:41:15] Bias-correcting 1 members separately...
[2021-10-29 16:41:15] Done.
Validation 3, 19 remaining
[2021-10-29 16:41:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:16] Number of windows considered: 1...
[2021-10-29 16:41:16] Bias-correcting 1 members separately...
[2021-10-29 16:41:16] Done.
Validation 4, 18 remaining
[2021-10-29 16:41:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:17] Number of windows considered: 1...
[2021-10-29 16:41:17] Bias-correcting 1 members separately...
[2021-10-29 16:41:17] Done.
Validation 5, 17 remaining
[2021-10-29 16:41:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:18] Number of windows considered: 1...
[2021-10-29 16:41:18] Bias-correcting 1 members separately...
[2021-10-29 16:41:18] Done.
Validation 6, 16 remaining
[2021-10-29 16:41:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:19] Number of windows considered: 1...
[2021-10-29 16:41:19] Bias-correcting 1 members separately...
[2021-10-29 16:41:19] Done.
Validation 7, 15 remaining
[2021-10-29 16:41:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:20] Number of windows considered: 1...
[2021-10-29 16:41:20] Bias-correcting 1 members separately...
[2021-10-29 16:41:20] Done.
Validation 8, 14 remaining
[2021-10-29 16:41:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:21] Number of windows considered: 1...
[2021-10-29 16:41:21] Bias-correcting 1 members separately...
[2021-10-29 16:41:21] Done.
Validation 9, 13 remaining
[2021-10-29 16:41:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:22] Number of windows considered: 1...
[2021-10-29 16:41:22] Bias-correcting 1 members separately...
[2021-10-29 16:41:22] Done.
Validation 10, 12 remaining
[2021-10-29 16:41:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:23] Number of windows considered: 1...
[2021-10-29 16:41:23] Bias-correcting 1 members separately...
[2021-10-29 16:41:23] Done.
Validation 11, 11 remaining
[2021-10-29 16:41:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:24] Number of windows considered: 1...
[2021-10-29 16:41:24] Bias-correcting 1 members separately...
[2021-10-29 16:41:24] Done.
Validation 12, 10 remaining
[2021-10-29 16:41:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:25] Number of windows considered: 1...
[2021-10-29 16:41:25] Bias-correcting 1 members separately...
[2021-10-29 16:41:25] Done.
Validation 13, 9 remaining
[2021-10-29 16:41:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:26] Number of windows considered: 1...
[2021-10-29 16:41:26] Bias-correcting 1 members separately...
[2021-10-29 16:41:26] Done.
Validation 14, 8 remaining
[2021-10-29 16:41:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:27] Number of windows considered: 1...
[2021-10-29 16:41:27] Bias-correcting 1 members separately...
[2021-10-29 16:41:27] Done.
Validation 15, 7 remaining
[2021-10-29 16:41:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:28] Number of windows considered: 1...
[2021-10-29 16:41:28] Bias-correcting 1 members separately...
[2021-10-29 16:41:28] Done.
Validation 16, 6 remaining
[2021-10-29 16:41:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:29] Number of windows considered: 1...
[2021-10-29 16:41:29] Bias-correcting 1 members separately...
[2021-10-29 16:41:29] Done.
Validation 17, 5 remaining
[2021-10-29 16:41:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:30] Number of windows considered: 1...
[2021-10-29 16:41:30] Bias-correcting 1 members separately...
[2021-10-29 16:41:31] Done.
Validation 18, 4 remaining
[2021-10-29 16:41:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:31] Number of windows considered: 1...
[2021-10-29 16:41:31] Bias-correcting 1 members separately...
[2021-10-29 16:41:32] Done.
Validation 19, 3 remaining
[2021-10-29 16:41:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:33] Number of windows considered: 1...
[2021-10-29 16:41:33] Bias-correcting 1 members separately...
[2021-10-29 16:41:33] Done.
Validation 20, 2 remaining
[2021-10-29 16:41:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:34] Number of windows considered: 1...
[2021-10-29 16:41:34] Bias-correcting 1 members separately...
[2021-10-29 16:41:34] Done.
Validation 21, 1 remaining
[2021-10-29 16:41:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:35] Number of windows considered: 1...
[2021-10-29 16:41:35] Bias-correcting 1 members separately...
[2021-10-29 16:41:35] Done.
Validation 22, 0 remaining
[2021-10-29 16:41:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:36] Number of windows considered: 1...
[2021-10-29 16:41:36] Bias-correcting 1 members separately...
[2021-10-29 16:41:36] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 16:41:36] Performing annual aggregation...
[2021-10-29 16:41:36] Done.
[2021-10-29 16:41:36] - Computing climatology...
[2021-10-29 16:41:36] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.eqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:41:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:38] Number of windows considered: 1...
[2021-10-29 16:41:38] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:41:38] Done.
Validation 2, 20 remaining
[2021-10-29 16:41:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:39] Number of windows considered: 1...
[2021-10-29 16:41:39] Bias-correcting 1 members separately...
[2021-10-29 16:41:39] Done.
Validation 3, 19 remaining
[2021-10-29 16:41:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:40] Number of windows considered: 1...
[2021-10-29 16:41:40] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:41:40] Done.
Validation 4, 18 remaining
[2021-10-29 16:41:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:41] Number of windows considered: 1...
[2021-10-29 16:41:41] Bias-correcting 1 members separately...
[2021-10-29 16:41:41] Done.
Validation 5, 17 remaining
[2021-10-29 16:41:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:42] Number of windows considered: 1...
[2021-10-29 16:41:42] Bias-correcting 1 members separately...
[2021-10-29 16:41:42] Done.
Validation 6, 16 remaining
[2021-10-29 16:41:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:43] Number of windows considered: 1...
[2021-10-29 16:41:43] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:41:43] Done.
Validation 7, 15 remaining
[2021-10-29 16:41:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:44] Number of windows considered: 1...
[2021-10-29 16:41:44] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:41:44] Done.
Validation 8, 14 remaining
[2021-10-29 16:41:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:45] Number of windows considered: 1...
[2021-10-29 16:41:45] Bias-correcting 1 members separately...
[2021-10-29 16:41:45] Done.
Validation 9, 13 remaining
[2021-10-29 16:41:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:47] Number of windows considered: 1...
[2021-10-29 16:41:47] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:41:47] Done.
Validation 10, 12 remaining
[2021-10-29 16:41:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:48] Number of windows considered: 1...
[2021-10-29 16:41:48] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:41:48] Done.
Validation 11, 11 remaining
[2021-10-29 16:41:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:49] Number of windows considered: 1...
[2021-10-29 16:41:49] Bias-correcting 1 members separately...
[2021-10-29 16:41:49] Done.
Validation 12, 10 remaining
[2021-10-29 16:41:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:50] Number of windows considered: 1...
[2021-10-29 16:41:50] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:41:50] Done.
Validation 13, 9 remaining
[2021-10-29 16:41:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:51] Number of windows considered: 1...
[2021-10-29 16:41:51] Bias-correcting 1 members separately...
[2021-10-29 16:41:51] Done.
Validation 14, 8 remaining
[2021-10-29 16:41:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:52] Number of windows considered: 1...
[2021-10-29 16:41:52] Bias-correcting 1 members separately...
[2021-10-29 16:41:52] Done.
Validation 15, 7 remaining
[2021-10-29 16:41:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:53] Number of windows considered: 1...
[2021-10-29 16:41:53] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:41:53] Done.
Validation 16, 6 remaining
[2021-10-29 16:41:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:54] Number of windows considered: 1...
[2021-10-29 16:41:54] Bias-correcting 1 members separately...
[2021-10-29 16:41:54] Done.
Validation 17, 5 remaining
[2021-10-29 16:41:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:55] Number of windows considered: 1...
[2021-10-29 16:41:55] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:41:55] Done.
Validation 18, 4 remaining
[2021-10-29 16:41:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:56] Number of windows considered: 1...
[2021-10-29 16:41:56] Bias-correcting 1 members separately...
[2021-10-29 16:41:56] Done.
Validation 19, 3 remaining
[2021-10-29 16:41:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:57] Number of windows considered: 1...
[2021-10-29 16:41:57] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:41:57] Done.
Validation 20, 2 remaining
[2021-10-29 16:41:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:41:59] Number of windows considered: 1...
[2021-10-29 16:41:59] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:41:59] Done.
Validation 21, 1 remaining
[2021-10-29 16:42:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:00] Number of windows considered: 1...
[2021-10-29 16:42:00] Bias-correcting 1 members separately...
[2021-10-29 16:42:00] Done.
Validation 22, 0 remaining
[2021-10-29 16:42:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:01] Number of windows considered: 1...
[2021-10-29 16:42:01] Bias-correcting 1 members separately...
[2021-10-29 16:42:01] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 16:42:01] Performing annual aggregation...
[2021-10-29 16:42:01] Done.
[2021-10-29 16:42:01] - Computing climatology...
[2021-10-29 16:42:01] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:42:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:03] Number of windows considered: 1...
[2021-10-29 16:42:03] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:42:03] Done.
Validation 2, 20 remaining
[2021-10-29 16:42:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:04] Number of windows considered: 1...
[2021-10-29 16:42:04] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 16:42:04] Done.
Validation 3, 19 remaining
[2021-10-29 16:42:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:05] Number of windows considered: 1...
[2021-10-29 16:42:05] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 16:42:05] Done.
Validation 4, 18 remaining
[2021-10-29 16:42:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:06] Number of windows considered: 1...
[2021-10-29 16:42:06] Bias-correcting 1 members separately...
[2021-10-29 16:42:06] Done.
Validation 5, 17 remaining
[2021-10-29 16:42:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:07] Number of windows considered: 1...
[2021-10-29 16:42:07] Bias-correcting 1 members separately...
[2021-10-29 16:42:07] Done.
Validation 6, 16 remaining
[2021-10-29 16:42:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:08] Number of windows considered: 1...
[2021-10-29 16:42:08] Bias-correcting 1 members separately...
[2021-10-29 16:42:08] Done.
Validation 7, 15 remaining
[2021-10-29 16:42:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:09] Number of windows considered: 1...
[2021-10-29 16:42:09] Bias-correcting 1 members separately...
[2021-10-29 16:42:09] Done.
Validation 8, 14 remaining
[2021-10-29 16:42:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:10] Number of windows considered: 1...
[2021-10-29 16:42:10] Bias-correcting 1 members separately...
[2021-10-29 16:42:10] Done.
Validation 9, 13 remaining
[2021-10-29 16:42:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:12] Number of windows considered: 1...
[2021-10-29 16:42:12] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:42:12] Done.
Validation 10, 12 remaining
[2021-10-29 16:42:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:13] Number of windows considered: 1...
[2021-10-29 16:42:13] Bias-correcting 1 members separately...
[2021-10-29 16:42:13] Done.
Validation 11, 11 remaining
[2021-10-29 16:42:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:14] Number of windows considered: 1...
[2021-10-29 16:42:14] Bias-correcting 1 members separately...
[2021-10-29 16:42:14] Done.
Validation 12, 10 remaining
[2021-10-29 16:42:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:15] Number of windows considered: 1...
[2021-10-29 16:42:15] Bias-correcting 1 members separately...
[2021-10-29 16:42:15] Done.
Validation 13, 9 remaining
[2021-10-29 16:42:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:16] Number of windows considered: 1...
[2021-10-29 16:42:16] Bias-correcting 1 members separately...
[2021-10-29 16:42:16] Done.
Validation 14, 8 remaining
[2021-10-29 16:42:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:17] Number of windows considered: 1...
[2021-10-29 16:42:17] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 16:42:17] Done.
Validation 15, 7 remaining
[2021-10-29 16:42:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:18] Number of windows considered: 1...
[2021-10-29 16:42:18] Bias-correcting 1 members separately...
[2021-10-29 16:42:18] Done.
Validation 16, 6 remaining
[2021-10-29 16:42:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:20] Number of windows considered: 1...
[2021-10-29 16:42:20] Bias-correcting 1 members separately...
[2021-10-29 16:42:20] Done.
Validation 17, 5 remaining
[2021-10-29 16:42:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:21] Number of windows considered: 1...
[2021-10-29 16:42:21] Bias-correcting 1 members separately...
[2021-10-29 16:42:21] Done.
Validation 18, 4 remaining
[2021-10-29 16:42:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:22] Number of windows considered: 1...
[2021-10-29 16:42:22] Bias-correcting 1 members separately...
[2021-10-29 16:42:22] Done.
Validation 19, 3 remaining
[2021-10-29 16:42:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:23] Number of windows considered: 1...
[2021-10-29 16:42:23] Bias-correcting 1 members separately...
[2021-10-29 16:42:23] Done.
Validation 20, 2 remaining
[2021-10-29 16:42:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:24] Number of windows considered: 1...
[2021-10-29 16:42:24] Bias-correcting 1 members separately...
[2021-10-29 16:42:24] Done.
Validation 21, 1 remaining
[2021-10-29 16:42:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:25] Number of windows considered: 1...
[2021-10-29 16:42:25] Bias-correcting 1 members separately...
[2021-10-29 16:42:25] Done.
Validation 22, 0 remaining
[2021-10-29 16:42:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:26] Number of windows considered: 1...
[2021-10-29 16:42:26] Bias-correcting 1 members separately...
[2021-10-29 16:42:27] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 16:42:27] Performing annual aggregation...
[2021-10-29 16:42:27] Done.
[2021-10-29 16:42:27] - Computing climatology...
[2021-10-29 16:42:27] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm2.cl3 <- index.cal.station.cl3
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
GPQM-WT3 EQM-WT3 PQM-WT3 GPQM2-WT3
0.5669590 0.5105306 0.5001543 0.4567808
scores.st2.wt3 <- scores
WT4
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))
station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
[2021-10-29 16:42:28] Performing annual aggregation...
[2021-10-29 16:42:28] Done.
[2021-10-29 16:42:28] - Computing climatology...
[2021-10-29 16:42:28] - Done.
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)
index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
[2021-10-29 16:42:28] Performing annual aggregation...
[2021-10-29 16:42:28] Done.
[2021-10-29 16:42:28] - Computing climatology...
[2021-10-29 16:42:28] - Done.
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")
station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:42:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:29] Number of windows considered: 1...
[2021-10-29 16:42:29] Bias-correcting 1 members separately...
[2021-10-29 16:42:29] Done.
Validation 2, 20 remaining
[2021-10-29 16:42:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:30] Number of windows considered: 1...
[2021-10-29 16:42:30] Bias-correcting 1 members separately...
[2021-10-29 16:42:30] Done.
Validation 3, 19 remaining
[2021-10-29 16:42:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:31] Number of windows considered: 1...
[2021-10-29 16:42:31] Bias-correcting 1 members separately...
[2021-10-29 16:42:31] Done.
Validation 4, 18 remaining
[2021-10-29 16:42:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:32] Number of windows considered: 1...
[2021-10-29 16:42:32] Bias-correcting 1 members separately...
[2021-10-29 16:42:32] Done.
Validation 5, 17 remaining
[2021-10-29 16:42:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:33] Number of windows considered: 1...
[2021-10-29 16:42:33] Bias-correcting 1 members separately...
[2021-10-29 16:42:33] Done.
Validation 6, 16 remaining
[2021-10-29 16:42:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:35] Number of windows considered: 1...
[2021-10-29 16:42:35] Bias-correcting 1 members separately...
[2021-10-29 16:42:35] Done.
Validation 7, 15 remaining
[2021-10-29 16:42:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:36] Number of windows considered: 1...
[2021-10-29 16:42:36] Bias-correcting 1 members separately...
[2021-10-29 16:42:36] Done.
Validation 8, 14 remaining
[2021-10-29 16:42:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:37] Number of windows considered: 1...
[2021-10-29 16:42:37] Bias-correcting 1 members separately...
[2021-10-29 16:42:37] Done.
Validation 9, 13 remaining
[2021-10-29 16:42:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:38] Number of windows considered: 1...
[2021-10-29 16:42:38] Bias-correcting 1 members separately...
[2021-10-29 16:42:38] Done.
Validation 10, 12 remaining
[2021-10-29 16:42:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:39] Number of windows considered: 1...
[2021-10-29 16:42:39] Bias-correcting 1 members separately...
[2021-10-29 16:42:39] Done.
Validation 11, 11 remaining
[2021-10-29 16:42:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:40] Number of windows considered: 1...
[2021-10-29 16:42:40] Bias-correcting 1 members separately...
[2021-10-29 16:42:40] Done.
Validation 12, 10 remaining
[2021-10-29 16:42:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:41] Number of windows considered: 1...
[2021-10-29 16:42:41] Bias-correcting 1 members separately...
[2021-10-29 16:42:41] Done.
Validation 13, 9 remaining
[2021-10-29 16:42:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:42] Number of windows considered: 1...
[2021-10-29 16:42:42] Bias-correcting 1 members separately...
[2021-10-29 16:42:42] Done.
Validation 14, 8 remaining
[2021-10-29 16:42:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:43] Number of windows considered: 1...
[2021-10-29 16:42:43] Bias-correcting 1 members separately...
[2021-10-29 16:42:43] Done.
Validation 15, 7 remaining
[2021-10-29 16:42:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:44] Number of windows considered: 1...
[2021-10-29 16:42:44] Bias-correcting 1 members separately...
[2021-10-29 16:42:44] Done.
Validation 16, 6 remaining
[2021-10-29 16:42:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:44] Number of windows considered: 1...
[2021-10-29 16:42:44] Bias-correcting 1 members separately...
[2021-10-29 16:42:45] Done.
Validation 17, 5 remaining
[2021-10-29 16:42:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:45] Number of windows considered: 1...
[2021-10-29 16:42:45] Bias-correcting 1 members separately...
[2021-10-29 16:42:45] Done.
Validation 18, 4 remaining
[2021-10-29 16:42:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:46] Number of windows considered: 1...
[2021-10-29 16:42:46] Bias-correcting 1 members separately...
[2021-10-29 16:42:46] Done.
Validation 19, 3 remaining
[2021-10-29 16:42:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:47] Number of windows considered: 1...
[2021-10-29 16:42:47] Bias-correcting 1 members separately...
[2021-10-29 16:42:47] Done.
Validation 20, 2 remaining
[2021-10-29 16:42:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:48] Number of windows considered: 1...
[2021-10-29 16:42:48] Bias-correcting 1 members separately...
[2021-10-29 16:42:48] Done.
Validation 21, 1 remaining
[2021-10-29 16:42:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:49] Number of windows considered: 1...
[2021-10-29 16:42:49] Bias-correcting 1 members separately...
[2021-10-29 16:42:49] Done.
Validation 22, 0 remaining
[2021-10-29 16:42:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:50] Number of windows considered: 1...
[2021-10-29 16:42:50] Bias-correcting 1 members separately...
[2021-10-29 16:42:50] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 16:42:51] Performing annual aggregation...
[2021-10-29 16:42:51] Done.
[2021-10-29 16:42:51] - Computing climatology...
[2021-10-29 16:42:51] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.pqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:42:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:52] Number of windows considered: 1...
[2021-10-29 16:42:52] Bias-correcting 1 members separately...
[2021-10-29 16:42:52] Done.
Validation 2, 20 remaining
[2021-10-29 16:42:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:53] Number of windows considered: 1...
[2021-10-29 16:42:53] Bias-correcting 1 members separately...
[2021-10-29 16:42:53] Done.
Validation 3, 19 remaining
[2021-10-29 16:42:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:54] Number of windows considered: 1...
[2021-10-29 16:42:54] Bias-correcting 1 members separately...
[2021-10-29 16:42:54] Done.
Validation 4, 18 remaining
[2021-10-29 16:42:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:55] Number of windows considered: 1...
[2021-10-29 16:42:55] Bias-correcting 1 members separately...
[2021-10-29 16:42:56] Done.
Validation 5, 17 remaining
[2021-10-29 16:42:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:57] Number of windows considered: 1...
[2021-10-29 16:42:57] Bias-correcting 1 members separately...
[2021-10-29 16:42:57] Done.
Validation 6, 16 remaining
[2021-10-29 16:42:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:58] Number of windows considered: 1...
[2021-10-29 16:42:58] Bias-correcting 1 members separately...
[2021-10-29 16:42:58] Done.
Validation 7, 15 remaining
[2021-10-29 16:42:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:42:59] Number of windows considered: 1...
[2021-10-29 16:42:59] Bias-correcting 1 members separately...
[2021-10-29 16:42:59] Done.
Validation 8, 14 remaining
[2021-10-29 16:43:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:00] Number of windows considered: 1...
[2021-10-29 16:43:00] Bias-correcting 1 members separately...
[2021-10-29 16:43:00] Done.
Validation 9, 13 remaining
[2021-10-29 16:43:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:01] Number of windows considered: 1...
[2021-10-29 16:43:01] Bias-correcting 1 members separately...
[2021-10-29 16:43:01] Done.
Validation 10, 12 remaining
[2021-10-29 16:43:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:02] Number of windows considered: 1...
[2021-10-29 16:43:02] Bias-correcting 1 members separately...
[2021-10-29 16:43:02] Done.
Validation 11, 11 remaining
[2021-10-29 16:43:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:03] Number of windows considered: 1...
[2021-10-29 16:43:03] Bias-correcting 1 members separately...
[2021-10-29 16:43:03] Done.
Validation 12, 10 remaining
[2021-10-29 16:43:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:04] Number of windows considered: 1...
[2021-10-29 16:43:04] Bias-correcting 1 members separately...
[2021-10-29 16:43:04] Done.
Validation 13, 9 remaining
[2021-10-29 16:43:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:05] Number of windows considered: 1...
[2021-10-29 16:43:05] Bias-correcting 1 members separately...
[2021-10-29 16:43:05] Done.
Validation 14, 8 remaining
[2021-10-29 16:43:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:06] Number of windows considered: 1...
[2021-10-29 16:43:06] Bias-correcting 1 members separately...
[2021-10-29 16:43:06] Done.
Validation 15, 7 remaining
[2021-10-29 16:43:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:07] Number of windows considered: 1...
[2021-10-29 16:43:07] Bias-correcting 1 members separately...
[2021-10-29 16:43:07] Done.
Validation 16, 6 remaining
[2021-10-29 16:43:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:08] Number of windows considered: 1...
[2021-10-29 16:43:08] Bias-correcting 1 members separately...
[2021-10-29 16:43:09] Done.
Validation 17, 5 remaining
[2021-10-29 16:43:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:10] Number of windows considered: 1...
[2021-10-29 16:43:10] Bias-correcting 1 members separately...
[2021-10-29 16:43:10] Done.
Validation 18, 4 remaining
[2021-10-29 16:43:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:11] Number of windows considered: 1...
[2021-10-29 16:43:11] Bias-correcting 1 members separately...
[2021-10-29 16:43:11] Done.
Validation 19, 3 remaining
[2021-10-29 16:43:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:12] Number of windows considered: 1...
[2021-10-29 16:43:12] Bias-correcting 1 members separately...
[2021-10-29 16:43:12] Done.
Validation 20, 2 remaining
[2021-10-29 16:43:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:13] Number of windows considered: 1...
[2021-10-29 16:43:13] Bias-correcting 1 members separately...
[2021-10-29 16:43:13] Done.
Validation 21, 1 remaining
[2021-10-29 16:43:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:14] Number of windows considered: 1...
[2021-10-29 16:43:14] Bias-correcting 1 members separately...
[2021-10-29 16:43:14] Done.
Validation 22, 0 remaining
[2021-10-29 16:43:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:16] Number of windows considered: 1...
[2021-10-29 16:43:16] Bias-correcting 1 members separately...
[2021-10-29 16:43:16] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 16:43:16] Performing annual aggregation...
[2021-10-29 16:43:16] Done.
[2021-10-29 16:43:16] - Computing climatology...
[2021-10-29 16:43:16] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.eqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:43:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:18] Number of windows considered: 1...
[2021-10-29 16:43:18] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:43:18] Done.
Validation 2, 20 remaining
[2021-10-29 16:43:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:19] Number of windows considered: 1...
[2021-10-29 16:43:19] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:43:19] Done.
Validation 3, 19 remaining
[2021-10-29 16:43:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:20] Number of windows considered: 1...
[2021-10-29 16:43:20] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:43:20] Done.
Validation 4, 18 remaining
[2021-10-29 16:43:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:21] Number of windows considered: 1...
[2021-10-29 16:43:21] Bias-correcting 1 members separately...
[2021-10-29 16:43:21] Done.
Validation 5, 17 remaining
[2021-10-29 16:43:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:22] Number of windows considered: 1...
[2021-10-29 16:43:22] Bias-correcting 1 members separately...
[2021-10-29 16:43:22] Done.
Validation 6, 16 remaining
[2021-10-29 16:43:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:24] Number of windows considered: 1...
[2021-10-29 16:43:24] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:43:24] Done.
Validation 7, 15 remaining
[2021-10-29 16:43:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:25] Number of windows considered: 1...
[2021-10-29 16:43:25] Bias-correcting 1 members separately...
[2021-10-29 16:43:25] Done.
Validation 8, 14 remaining
[2021-10-29 16:43:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:26] Number of windows considered: 1...
[2021-10-29 16:43:26] Bias-correcting 1 members separately...
[2021-10-29 16:43:26] Done.
Validation 9, 13 remaining
[2021-10-29 16:43:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:27] Number of windows considered: 1...
[2021-10-29 16:43:27] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:43:27] Done.
Validation 10, 12 remaining
[2021-10-29 16:43:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:28] Number of windows considered: 1...
[2021-10-29 16:43:28] Bias-correcting 1 members separately...
[2021-10-29 16:43:28] Done.
Validation 11, 11 remaining
[2021-10-29 16:43:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:29] Number of windows considered: 1...
[2021-10-29 16:43:29] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:43:29] Done.
Validation 12, 10 remaining
[2021-10-29 16:43:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:30] Number of windows considered: 1...
[2021-10-29 16:43:30] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:43:30] Done.
Validation 13, 9 remaining
[2021-10-29 16:43:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:31] Number of windows considered: 1...
[2021-10-29 16:43:31] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:43:31] Done.
Validation 14, 8 remaining
[2021-10-29 16:43:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:32] Number of windows considered: 1...
[2021-10-29 16:43:32] Bias-correcting 1 members separately...
[2021-10-29 16:43:32] Done.
Validation 15, 7 remaining
[2021-10-29 16:43:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:33] Number of windows considered: 1...
[2021-10-29 16:43:33] Bias-correcting 1 members separately...
[2021-10-29 16:43:33] Done.
Validation 16, 6 remaining
[2021-10-29 16:43:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:35] Number of windows considered: 1...
[2021-10-29 16:43:35] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:43:35] Done.
Validation 17, 5 remaining
[2021-10-29 16:43:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:36] Number of windows considered: 1...
[2021-10-29 16:43:36] Bias-correcting 1 members separately...
[2021-10-29 16:43:36] Done.
Validation 18, 4 remaining
[2021-10-29 16:43:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:37] Number of windows considered: 1...
[2021-10-29 16:43:37] Bias-correcting 1 members separately...
[2021-10-29 16:43:37] Done.
Validation 19, 3 remaining
[2021-10-29 16:43:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:38] Number of windows considered: 1...
[2021-10-29 16:43:38] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:43:38] Done.
Validation 20, 2 remaining
[2021-10-29 16:43:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:39] Number of windows considered: 1...
[2021-10-29 16:43:39] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:43:39] Done.
Validation 21, 1 remaining
[2021-10-29 16:43:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:40] Number of windows considered: 1...
[2021-10-29 16:43:40] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:43:40] Done.
Validation 22, 0 remaining
[2021-10-29 16:43:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:42] Number of windows considered: 1...
[2021-10-29 16:43:42] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:43:42] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 16:43:42] Performing annual aggregation...
[2021-10-29 16:43:42] Done.
[2021-10-29 16:43:42] - Computing climatology...
[2021-10-29 16:43:42] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:43:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:44] Number of windows considered: 1...
[2021-10-29 16:43:44] Bias-correcting 1 members separately...
[2021-10-29 16:43:44] Done.
Validation 2, 20 remaining
[2021-10-29 16:43:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:45] Number of windows considered: 1...
[2021-10-29 16:43:45] Bias-correcting 1 members separately...
[2021-10-29 16:43:45] Done.
Validation 3, 19 remaining
[2021-10-29 16:43:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:46] Number of windows considered: 1...
[2021-10-29 16:43:46] Bias-correcting 1 members separately...
[2021-10-29 16:43:46] Done.
Validation 4, 18 remaining
[2021-10-29 16:43:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:47] Number of windows considered: 1...
[2021-10-29 16:43:47] Bias-correcting 1 members separately...
[2021-10-29 16:43:47] Done.
Validation 5, 17 remaining
[2021-10-29 16:43:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:48] Number of windows considered: 1...
[2021-10-29 16:43:48] Bias-correcting 1 members separately...
[2021-10-29 16:43:49] Done.
Validation 6, 16 remaining
[2021-10-29 16:43:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:50] Number of windows considered: 1...
[2021-10-29 16:43:50] Bias-correcting 1 members separately...
[2021-10-29 16:43:50] Done.
Validation 7, 15 remaining
[2021-10-29 16:43:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:51] Number of windows considered: 1...
[2021-10-29 16:43:51] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:43:51] Done.
Validation 8, 14 remaining
[2021-10-29 16:43:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:52] Number of windows considered: 1...
[2021-10-29 16:43:52] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:43:52] Done.
Validation 9, 13 remaining
[2021-10-29 16:43:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:53] Number of windows considered: 1...
[2021-10-29 16:43:53] Bias-correcting 1 members separately...
[2021-10-29 16:43:53] Done.
Validation 10, 12 remaining
[2021-10-29 16:43:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:54] Number of windows considered: 1...
[2021-10-29 16:43:54] Bias-correcting 1 members separately...
[2021-10-29 16:43:54] Done.
Validation 11, 11 remaining
[2021-10-29 16:43:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:55] Number of windows considered: 1...
[2021-10-29 16:43:55] Bias-correcting 1 members separately...
[2021-10-29 16:43:55] Done.
Validation 12, 10 remaining
[2021-10-29 16:43:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:56] Number of windows considered: 1...
[2021-10-29 16:43:56] Bias-correcting 1 members separately...
[2021-10-29 16:43:57] Done.
Validation 13, 9 remaining
[2021-10-29 16:43:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:58] Number of windows considered: 1...
[2021-10-29 16:43:58] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:43:58] Done.
Validation 14, 8 remaining
[2021-10-29 16:43:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:43:59] Number of windows considered: 1...
[2021-10-29 16:43:59] Bias-correcting 1 members separately...
[2021-10-29 16:43:59] Done.
Validation 15, 7 remaining
[2021-10-29 16:44:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:00] Number of windows considered: 1...
[2021-10-29 16:44:00] Bias-correcting 1 members separately...
[2021-10-29 16:44:00] Done.
Validation 16, 6 remaining
[2021-10-29 16:44:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:01] Number of windows considered: 1...
[2021-10-29 16:44:01] Bias-correcting 1 members separately...
[2021-10-29 16:44:01] Done.
Validation 17, 5 remaining
[2021-10-29 16:44:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:02] Number of windows considered: 1...
[2021-10-29 16:44:02] Bias-correcting 1 members separately...
[2021-10-29 16:44:02] Done.
Validation 18, 4 remaining
[2021-10-29 16:44:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:03] Number of windows considered: 1...
[2021-10-29 16:44:03] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:44:04] Done.
Validation 19, 3 remaining
[2021-10-29 16:44:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:05] Number of windows considered: 1...
[2021-10-29 16:44:05] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:44:05] Done.
Validation 20, 2 remaining
[2021-10-29 16:44:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:06] Number of windows considered: 1...
[2021-10-29 16:44:06] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 16:44:06] Done.
Validation 21, 1 remaining
[2021-10-29 16:44:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:07] Number of windows considered: 1...
[2021-10-29 16:44:07] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:44:07] Done.
Validation 22, 0 remaining
[2021-10-29 16:44:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:08] Number of windows considered: 1...
[2021-10-29 16:44:08] Bias-correcting 1 members separately...
[2021-10-29 16:44:08] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 16:44:09] Performing annual aggregation...
[2021-10-29 16:44:09] Done.
[2021-10-29 16:44:09] - Computing climatology...
[2021-10-29 16:44:09] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm2.cl4 <- index.cal.station.cl4
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)
scores
PQM-WT4 EQM-WT4 GPQM2-WT4 GPQM-WT4
0.7106158 0.6367193 0.3657862 0.3346539
scores.st2.wt4 <- scores
WT5
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))
station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
[2021-10-29 16:44:10] Performing annual aggregation...
[2021-10-29 16:44:10] Done.
[2021-10-29 16:44:10] - Computing climatology...
[2021-10-29 16:44:10] - Done.
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)
index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
[2021-10-29 16:44:10] Performing annual aggregation...
[2021-10-29 16:44:10] Done.
[2021-10-29 16:44:10] - Computing climatology...
[2021-10-29 16:44:10] - Done.
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")
station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:44:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:11] Number of windows considered: 1...
[2021-10-29 16:44:11] Bias-correcting 1 members separately...
[2021-10-29 16:44:11] Done.
Validation 2, 20 remaining
[2021-10-29 16:44:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:12] Number of windows considered: 1...
[2021-10-29 16:44:12] Bias-correcting 1 members separately...
[2021-10-29 16:44:12] Done.
Validation 3, 19 remaining
[2021-10-29 16:44:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:14] Number of windows considered: 1...
[2021-10-29 16:44:14] Bias-correcting 1 members separately...
[2021-10-29 16:44:14] Done.
Validation 4, 18 remaining
[2021-10-29 16:44:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:15] Number of windows considered: 1...
[2021-10-29 16:44:15] Bias-correcting 1 members separately...
[2021-10-29 16:44:15] Done.
Validation 5, 17 remaining
[2021-10-29 16:44:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:15] Number of windows considered: 1...
[2021-10-29 16:44:15] Bias-correcting 1 members separately...
[2021-10-29 16:44:16] Done.
Validation 6, 16 remaining
[2021-10-29 16:44:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:16] Number of windows considered: 1...
[2021-10-29 16:44:16] Bias-correcting 1 members separately...
[2021-10-29 16:44:16] Done.
Validation 7, 15 remaining
[2021-10-29 16:44:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:17] Number of windows considered: 1...
[2021-10-29 16:44:17] Bias-correcting 1 members separately...
[2021-10-29 16:44:17] Done.
Validation 8, 14 remaining
[2021-10-29 16:44:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:18] Number of windows considered: 1...
[2021-10-29 16:44:18] Bias-correcting 1 members separately...
[2021-10-29 16:44:18] Done.
Validation 9, 13 remaining
[2021-10-29 16:44:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:19] Number of windows considered: 1...
[2021-10-29 16:44:19] Bias-correcting 1 members separately...
[2021-10-29 16:44:19] Done.
Validation 10, 12 remaining
[2021-10-29 16:44:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:20] Number of windows considered: 1...
[2021-10-29 16:44:20] Bias-correcting 1 members separately...
[2021-10-29 16:44:20] Done.
Validation 11, 11 remaining
[2021-10-29 16:44:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:21] Number of windows considered: 1...
[2021-10-29 16:44:21] Bias-correcting 1 members separately...
[2021-10-29 16:44:21] Done.
Validation 12, 10 remaining
[2021-10-29 16:44:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:22] Number of windows considered: 1...
[2021-10-29 16:44:22] Bias-correcting 1 members separately...
[2021-10-29 16:44:22] Done.
Validation 13, 9 remaining
[2021-10-29 16:44:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:23] Number of windows considered: 1...
[2021-10-29 16:44:23] Bias-correcting 1 members separately...
[2021-10-29 16:44:23] Done.
Validation 14, 8 remaining
[2021-10-29 16:44:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:24] Number of windows considered: 1...
[2021-10-29 16:44:24] Bias-correcting 1 members separately...
[2021-10-29 16:44:24] Done.
Validation 15, 7 remaining
[2021-10-29 16:44:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:25] Number of windows considered: 1...
[2021-10-29 16:44:25] Bias-correcting 1 members separately...
[2021-10-29 16:44:25] Done.
Validation 16, 6 remaining
[2021-10-29 16:44:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:25] Number of windows considered: 1...
[2021-10-29 16:44:25] Bias-correcting 1 members separately...
[2021-10-29 16:44:26] Done.
Validation 17, 5 remaining
[2021-10-29 16:44:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:27] Number of windows considered: 1...
[2021-10-29 16:44:27] Bias-correcting 1 members separately...
[2021-10-29 16:44:27] Done.
Validation 18, 4 remaining
[2021-10-29 16:44:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:28] Number of windows considered: 1...
[2021-10-29 16:44:28] Bias-correcting 1 members separately...
[2021-10-29 16:44:28] Done.
Validation 19, 3 remaining
[2021-10-29 16:44:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:29] Number of windows considered: 1...
[2021-10-29 16:44:29] Bias-correcting 1 members separately...
[2021-10-29 16:44:29] Done.
Validation 20, 2 remaining
[2021-10-29 16:44:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:30] Number of windows considered: 1...
[2021-10-29 16:44:30] Bias-correcting 1 members separately...
[2021-10-29 16:44:30] Done.
Validation 21, 1 remaining
[2021-10-29 16:44:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:31] Number of windows considered: 1...
[2021-10-29 16:44:31] Bias-correcting 1 members separately...
[2021-10-29 16:44:31] Done.
Validation 22, 0 remaining
[2021-10-29 16:44:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:32] Number of windows considered: 1...
[2021-10-29 16:44:32] Bias-correcting 1 members separately...
[2021-10-29 16:44:32] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 16:44:32] Performing annual aggregation...
[2021-10-29 16:44:32] Done.
[2021-10-29 16:44:32] - Computing climatology...
[2021-10-29 16:44:32] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.pqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:44:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:34] Number of windows considered: 1...
[2021-10-29 16:44:34] Bias-correcting 1 members separately...
[2021-10-29 16:44:34] Done.
Validation 2, 20 remaining
[2021-10-29 16:44:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:35] Number of windows considered: 1...
[2021-10-29 16:44:35] Bias-correcting 1 members separately...
[2021-10-29 16:44:35] Done.
Validation 3, 19 remaining
[2021-10-29 16:44:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:36] Number of windows considered: 1...
[2021-10-29 16:44:36] Bias-correcting 1 members separately...
[2021-10-29 16:44:36] Done.
Validation 4, 18 remaining
[2021-10-29 16:44:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:37] Number of windows considered: 1...
[2021-10-29 16:44:37] Bias-correcting 1 members separately...
[2021-10-29 16:44:37] Done.
Validation 5, 17 remaining
[2021-10-29 16:44:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:38] Number of windows considered: 1...
[2021-10-29 16:44:38] Bias-correcting 1 members separately...
[2021-10-29 16:44:38] Done.
Validation 6, 16 remaining
[2021-10-29 16:44:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:39] Number of windows considered: 1...
[2021-10-29 16:44:39] Bias-correcting 1 members separately...
[2021-10-29 16:44:39] Done.
Validation 7, 15 remaining
[2021-10-29 16:44:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:40] Number of windows considered: 1...
[2021-10-29 16:44:40] Bias-correcting 1 members separately...
[2021-10-29 16:44:40] Done.
Validation 8, 14 remaining
[2021-10-29 16:44:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:41] Number of windows considered: 1...
[2021-10-29 16:44:41] Bias-correcting 1 members separately...
[2021-10-29 16:44:41] Done.
Validation 9, 13 remaining
[2021-10-29 16:44:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:42] Number of windows considered: 1...
[2021-10-29 16:44:42] Bias-correcting 1 members separately...
[2021-10-29 16:44:42] Done.
Validation 10, 12 remaining
[2021-10-29 16:44:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:44] Number of windows considered: 1...
[2021-10-29 16:44:44] Bias-correcting 1 members separately...
[2021-10-29 16:44:44] Done.
Validation 11, 11 remaining
[2021-10-29 16:44:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:45] Number of windows considered: 1...
[2021-10-29 16:44:45] Bias-correcting 1 members separately...
[2021-10-29 16:44:45] Done.
Validation 12, 10 remaining
[2021-10-29 16:44:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:46] Number of windows considered: 1...
[2021-10-29 16:44:46] Bias-correcting 1 members separately...
[2021-10-29 16:44:46] Done.
Validation 13, 9 remaining
[2021-10-29 16:44:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:47] Number of windows considered: 1...
[2021-10-29 16:44:47] Bias-correcting 1 members separately...
[2021-10-29 16:44:47] Done.
Validation 14, 8 remaining
[2021-10-29 16:44:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:48] Number of windows considered: 1...
[2021-10-29 16:44:48] Bias-correcting 1 members separately...
[2021-10-29 16:44:48] Done.
Validation 15, 7 remaining
[2021-10-29 16:44:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:49] Number of windows considered: 1...
[2021-10-29 16:44:49] Bias-correcting 1 members separately...
[2021-10-29 16:44:49] Done.
Validation 16, 6 remaining
[2021-10-29 16:44:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:50] Number of windows considered: 1...
[2021-10-29 16:44:50] Bias-correcting 1 members separately...
[2021-10-29 16:44:51] Done.
Validation 17, 5 remaining
[2021-10-29 16:44:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:52] Number of windows considered: 1...
[2021-10-29 16:44:52] Bias-correcting 1 members separately...
[2021-10-29 16:44:52] Done.
Validation 18, 4 remaining
[2021-10-29 16:44:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:53] Number of windows considered: 1...
[2021-10-29 16:44:53] Bias-correcting 1 members separately...
[2021-10-29 16:44:53] Done.
Validation 19, 3 remaining
[2021-10-29 16:44:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:54] Number of windows considered: 1...
[2021-10-29 16:44:54] Bias-correcting 1 members separately...
[2021-10-29 16:44:54] Done.
Validation 20, 2 remaining
[2021-10-29 16:44:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:55] Number of windows considered: 1...
[2021-10-29 16:44:55] Bias-correcting 1 members separately...
[2021-10-29 16:44:55] Done.
Validation 21, 1 remaining
[2021-10-29 16:44:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:56] Number of windows considered: 1...
[2021-10-29 16:44:56] Bias-correcting 1 members separately...
[2021-10-29 16:44:56] Done.
Validation 22, 0 remaining
[2021-10-29 16:44:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:57] Number of windows considered: 1...
[2021-10-29 16:44:57] Bias-correcting 1 members separately...
[2021-10-29 16:44:57] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 16:44:58] Performing annual aggregation...
[2021-10-29 16:44:58] Done.
[2021-10-29 16:44:58] - Computing climatology...
[2021-10-29 16:44:58] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.eqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:44:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:44:59] Number of windows considered: 1...
[2021-10-29 16:44:59] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:00] Done.
Validation 2, 20 remaining
[2021-10-29 16:45:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:01] Number of windows considered: 1...
[2021-10-29 16:45:01] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:01] Done.
Validation 3, 19 remaining
[2021-10-29 16:45:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:02] Number of windows considered: 1...
[2021-10-29 16:45:02] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:02] Done.
Validation 4, 18 remaining
[2021-10-29 16:45:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:03] Number of windows considered: 1...
[2021-10-29 16:45:03] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:03] Done.
Validation 5, 17 remaining
[2021-10-29 16:45:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:04] Number of windows considered: 1...
[2021-10-29 16:45:04] Bias-correcting 1 members separately...
[2021-10-29 16:45:04] Done.
Validation 6, 16 remaining
[2021-10-29 16:45:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:05] Number of windows considered: 1...
[2021-10-29 16:45:05] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:05] Done.
Validation 7, 15 remaining
[2021-10-29 16:45:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:06] Number of windows considered: 1...
[2021-10-29 16:45:06] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:06] Done.
Validation 8, 14 remaining
[2021-10-29 16:45:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:07] Number of windows considered: 1...
[2021-10-29 16:45:07] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:07] Done.
Validation 9, 13 remaining
[2021-10-29 16:45:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:09] Number of windows considered: 1...
[2021-10-29 16:45:09] Bias-correcting 1 members separately...
[2021-10-29 16:45:09] Done.
Validation 10, 12 remaining
[2021-10-29 16:45:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:10] Number of windows considered: 1...
[2021-10-29 16:45:10] Bias-correcting 1 members separately...
[2021-10-29 16:45:10] Done.
Validation 11, 11 remaining
[2021-10-29 16:45:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:11] Number of windows considered: 1...
[2021-10-29 16:45:11] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:45:11] Done.
Validation 12, 10 remaining
[2021-10-29 16:45:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:12] Number of windows considered: 1...
[2021-10-29 16:45:12] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:12] Done.
Validation 13, 9 remaining
[2021-10-29 16:45:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:13] Number of windows considered: 1...
[2021-10-29 16:45:13] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:14] Done.
Validation 14, 8 remaining
[2021-10-29 16:45:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:15] Number of windows considered: 1...
[2021-10-29 16:45:15] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:15] Done.
Validation 15, 7 remaining
[2021-10-29 16:45:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:16] Number of windows considered: 1...
[2021-10-29 16:45:16] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:16] Done.
Validation 16, 6 remaining
[2021-10-29 16:45:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:17] Number of windows considered: 1...
[2021-10-29 16:45:17] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:17] Done.
Validation 17, 5 remaining
[2021-10-29 16:45:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:18] Number of windows considered: 1...
[2021-10-29 16:45:18] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:45:18] Done.
Validation 18, 4 remaining
[2021-10-29 16:45:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:19] Number of windows considered: 1...
[2021-10-29 16:45:19] Bias-correcting 1 members separately...
[2021-10-29 16:45:20] Done.
Validation 19, 3 remaining
[2021-10-29 16:45:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:21] Number of windows considered: 1...
[2021-10-29 16:45:21] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:21] Done.
Validation 20, 2 remaining
[2021-10-29 16:45:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:22] Number of windows considered: 1...
[2021-10-29 16:45:22] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:22] Done.
Validation 21, 1 remaining
[2021-10-29 16:45:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:23] Number of windows considered: 1...
[2021-10-29 16:45:23] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:45:23] Done.
Validation 22, 0 remaining
[2021-10-29 16:45:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:24] Number of windows considered: 1...
[2021-10-29 16:45:24] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:45:24] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 16:45:25] Performing annual aggregation...
[2021-10-29 16:45:25] Done.
[2021-10-29 16:45:25] - Computing climatology...
[2021-10-29 16:45:25] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 16:45:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:27] Number of windows considered: 1...
[2021-10-29 16:45:27] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 16:45:27] Done.
Validation 2, 20 remaining
[2021-10-29 16:45:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:28] Number of windows considered: 1...
[2021-10-29 16:45:28] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 16:45:28] Done.
Validation 3, 19 remaining
[2021-10-29 16:45:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:29] Number of windows considered: 1...
[2021-10-29 16:45:29] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 16:45:29] Done.
Validation 4, 18 remaining
[2021-10-29 16:45:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:30] Number of windows considered: 1...
[2021-10-29 16:45:30] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 16:45:30] Done.
Validation 5, 17 remaining
[2021-10-29 16:45:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:31] Number of windows considered: 1...
[2021-10-29 16:45:31] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 16:45:32] Done.
Validation 6, 16 remaining
[2021-10-29 16:45:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:33] Number of windows considered: 1...
[2021-10-29 16:45:33] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 16:45:33] Done.
Validation 7, 15 remaining
[2021-10-29 16:45:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:34] Number of windows considered: 1...
[2021-10-29 16:45:34] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 16:45:34] Done.
Validation 8, 14 remaining
[2021-10-29 16:45:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:35] Number of windows considered: 1...
[2021-10-29 16:45:35] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 16:45:35] Done.
Validation 9, 13 remaining
[2021-10-29 16:45:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:36] Number of windows considered: 1...
[2021-10-29 16:45:36] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 16:45:36] Done.
Validation 10, 12 remaining
[2021-10-29 16:45:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:38] Number of windows considered: 1...
[2021-10-29 16:45:38] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 16:45:38] Done.
Validation 11, 11 remaining
[2021-10-29 16:45:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:39] Number of windows considered: 1...
[2021-10-29 16:45:39] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 16:45:39] Done.
Validation 12, 10 remaining
[2021-10-29 16:45:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:40] Number of windows considered: 1...
[2021-10-29 16:45:40] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 16:45:40] Done.
Validation 13, 9 remaining
[2021-10-29 16:45:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:41] Number of windows considered: 1...
[2021-10-29 16:45:41] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 16:45:41] Done.
Validation 14, 8 remaining
[2021-10-29 16:45:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:42] Number of windows considered: 1...
[2021-10-29 16:45:42] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 16:45:42] Done.
Validation 15, 7 remaining
[2021-10-29 16:45:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:43] Number of windows considered: 1...
[2021-10-29 16:45:43] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 16:45:43] Done.
Validation 16, 6 remaining
[2021-10-29 16:45:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:44] Number of windows considered: 1...
[2021-10-29 16:45:44] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 16:45:44] Done.
Validation 17, 5 remaining
[2021-10-29 16:45:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:45] Number of windows considered: 1...
[2021-10-29 16:45:45] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 16:45:45] Done.
Validation 18, 4 remaining
[2021-10-29 16:45:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:46] Number of windows considered: 1...
[2021-10-29 16:45:46] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 16:45:46] Done.
Validation 19, 3 remaining
[2021-10-29 16:45:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:47] Number of windows considered: 1...
[2021-10-29 16:45:47] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 16:45:47] Done.
Validation 20, 2 remaining
[2021-10-29 16:45:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:48] Number of windows considered: 1...
[2021-10-29 16:45:48] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 16:45:48] Done.
Validation 21, 1 remaining
[2021-10-29 16:45:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:49] Number of windows considered: 1...
[2021-10-29 16:45:49] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 16:45:49] Done.
Validation 22, 0 remaining
[2021-10-29 16:45:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:50] Number of windows considered: 1...
[2021-10-29 16:45:50] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 16:45:50] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 16:45:51] Performing annual aggregation...
[2021-10-29 16:45:51] Done.
[2021-10-29 16:45:51] - Computing climatology...
[2021-10-29 16:45:51] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm2.cl5 <- index.cal.station.cl5
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
EQM-WT5 GPQM-WT5 PQM-WT5 GPQM2-WT5
0.7232343 0.5088837 0.4973953 0.4946990
scores.st2.wt5 <- scores
Complete period (WO WTs)
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
[2021-10-29 16:45:52] Performing annual aggregation...
[2021-10-29 16:45:52] Done.
[2021-10-29 16:45:52] - Computing climatology...
[2021-10-29 16:45:52] - Done.
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)
index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
[2021-10-29 16:45:52] Performing annual aggregation...
[2021-10-29 16:45:52] Done.
[2021-10-29 16:45:52] - Computing climatology...
[2021-10-29 16:45:52] - Done.
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "pqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-10-29 16:45:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:53] Number of windows considered: 1...
[2021-10-29 16:45:53] Bias-correcting 1 members separately...
[2021-10-29 16:45:53] Done.
Validation 2, 20 remaining
[2021-10-29 16:45:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:54] Number of windows considered: 1...
[2021-10-29 16:45:54] Bias-correcting 1 members separately...
[2021-10-29 16:45:54] Done.
Validation 3, 19 remaining
[2021-10-29 16:45:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:55] Number of windows considered: 1...
[2021-10-29 16:45:55] Bias-correcting 1 members separately...
[2021-10-29 16:45:55] Done.
Validation 4, 18 remaining
[2021-10-29 16:45:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:56] Number of windows considered: 1...
[2021-10-29 16:45:56] Bias-correcting 1 members separately...
[2021-10-29 16:45:56] Done.
Validation 5, 17 remaining
[2021-10-29 16:45:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:57] Number of windows considered: 1...
[2021-10-29 16:45:57] Bias-correcting 1 members separately...
[2021-10-29 16:45:58] Done.
Validation 6, 16 remaining
[2021-10-29 16:45:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:58] Number of windows considered: 1...
[2021-10-29 16:45:58] Bias-correcting 1 members separately...
[2021-10-29 16:45:58] Done.
Validation 7, 15 remaining
[2021-10-29 16:45:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:45:59] Number of windows considered: 1...
[2021-10-29 16:45:59] Bias-correcting 1 members separately...
[2021-10-29 16:45:59] Done.
Validation 8, 14 remaining
[2021-10-29 16:46:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:01] Number of windows considered: 1...
[2021-10-29 16:46:01] Bias-correcting 1 members separately...
[2021-10-29 16:46:01] Done.
Validation 9, 13 remaining
[2021-10-29 16:46:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:02] Number of windows considered: 1...
[2021-10-29 16:46:02] Bias-correcting 1 members separately...
[2021-10-29 16:46:02] Done.
Validation 10, 12 remaining
[2021-10-29 16:46:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:03] Number of windows considered: 1...
[2021-10-29 16:46:03] Bias-correcting 1 members separately...
[2021-10-29 16:46:03] Done.
Validation 11, 11 remaining
[2021-10-29 16:46:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:04] Number of windows considered: 1...
[2021-10-29 16:46:04] Bias-correcting 1 members separately...
[2021-10-29 16:46:04] Done.
Validation 12, 10 remaining
[2021-10-29 16:46:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:05] Number of windows considered: 1...
[2021-10-29 16:46:05] Bias-correcting 1 members separately...
[2021-10-29 16:46:05] Done.
Validation 13, 9 remaining
[2021-10-29 16:46:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:06] Number of windows considered: 1...
[2021-10-29 16:46:06] Bias-correcting 1 members separately...
[2021-10-29 16:46:06] Done.
Validation 14, 8 remaining
[2021-10-29 16:46:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:07] Number of windows considered: 1...
[2021-10-29 16:46:07] Bias-correcting 1 members separately...
[2021-10-29 16:46:07] Done.
Validation 15, 7 remaining
[2021-10-29 16:46:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:08] Number of windows considered: 1...
[2021-10-29 16:46:08] Bias-correcting 1 members separately...
[2021-10-29 16:46:08] Done.
Validation 16, 6 remaining
[2021-10-29 16:46:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:09] Number of windows considered: 1...
[2021-10-29 16:46:09] Bias-correcting 1 members separately...
[2021-10-29 16:46:09] Done.
Validation 17, 5 remaining
[2021-10-29 16:46:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:10] Number of windows considered: 1...
[2021-10-29 16:46:10] Bias-correcting 1 members separately...
[2021-10-29 16:46:10] Done.
Validation 18, 4 remaining
[2021-10-29 16:46:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:11] Number of windows considered: 1...
[2021-10-29 16:46:11] Bias-correcting 1 members separately...
[2021-10-29 16:46:11] Done.
Validation 19, 3 remaining
[2021-10-29 16:46:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:12] Number of windows considered: 1...
[2021-10-29 16:46:12] Bias-correcting 1 members separately...
[2021-10-29 16:46:13] Done.
Validation 20, 2 remaining
[2021-10-29 16:46:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:14] Number of windows considered: 1...
[2021-10-29 16:46:14] Bias-correcting 1 members separately...
[2021-10-29 16:46:14] Done.
Validation 21, 1 remaining
[2021-10-29 16:46:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:15] Number of windows considered: 1...
[2021-10-29 16:46:15] Bias-correcting 1 members separately...
[2021-10-29 16:46:15] Done.
Validation 22, 0 remaining
[2021-10-29 16:46:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:16] Number of windows considered: 1...
[2021-10-29 16:46:16] Bias-correcting 1 members separately...
[2021-10-29 16:46:16] Done.
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 16:46:17] Performing annual aggregation...
[2021-10-29 16:46:17] Done.
[2021-10-29 16:46:17] - Computing climatology...
[2021-10-29 16:46:17] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.pqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "eqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-10-29 16:46:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:18] Number of windows considered: 1...
[2021-10-29 16:46:18] Bias-correcting 1 members separately...
[2021-10-29 16:46:18] Done.
Validation 2, 20 remaining
[2021-10-29 16:46:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:19] Number of windows considered: 1...
[2021-10-29 16:46:19] Bias-correcting 1 members separately...
[2021-10-29 16:46:19] Done.
Validation 3, 19 remaining
[2021-10-29 16:46:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:20] Number of windows considered: 1...
[2021-10-29 16:46:20] Bias-correcting 1 members separately...
[2021-10-29 16:46:21] Done.
Validation 4, 18 remaining
[2021-10-29 16:46:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:22] Number of windows considered: 1...
[2021-10-29 16:46:22] Bias-correcting 1 members separately...
[2021-10-29 16:46:22] Done.
Validation 5, 17 remaining
[2021-10-29 16:46:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:23] Number of windows considered: 1...
[2021-10-29 16:46:23] Bias-correcting 1 members separately...
[2021-10-29 16:46:24] Done.
Validation 6, 16 remaining
[2021-10-29 16:46:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:25] Number of windows considered: 1...
[2021-10-29 16:46:25] Bias-correcting 1 members separately...
[2021-10-29 16:46:25] Done.
Validation 7, 15 remaining
[2021-10-29 16:46:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:26] Number of windows considered: 1...
[2021-10-29 16:46:26] Bias-correcting 1 members separately...
[2021-10-29 16:46:26] Done.
Validation 8, 14 remaining
[2021-10-29 16:46:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:27] Number of windows considered: 1...
[2021-10-29 16:46:27] Bias-correcting 1 members separately...
[2021-10-29 16:46:27] Done.
Validation 9, 13 remaining
[2021-10-29 16:46:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:28] Number of windows considered: 1...
[2021-10-29 16:46:28] Bias-correcting 1 members separately...
[2021-10-29 16:46:29] Done.
Validation 10, 12 remaining
[2021-10-29 16:46:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:30] Number of windows considered: 1...
[2021-10-29 16:46:30] Bias-correcting 1 members separately...
[2021-10-29 16:46:30] Done.
Validation 11, 11 remaining
[2021-10-29 16:46:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:31] Number of windows considered: 1...
[2021-10-29 16:46:31] Bias-correcting 1 members separately...
[2021-10-29 16:46:31] Done.
Validation 12, 10 remaining
[2021-10-29 16:46:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:33] Number of windows considered: 1...
[2021-10-29 16:46:33] Bias-correcting 1 members separately...
[2021-10-29 16:46:33] Done.
Validation 13, 9 remaining
[2021-10-29 16:46:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:34] Number of windows considered: 1...
[2021-10-29 16:46:34] Bias-correcting 1 members separately...
[2021-10-29 16:46:34] Done.
Validation 14, 8 remaining
[2021-10-29 16:46:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:35] Number of windows considered: 1...
[2021-10-29 16:46:35] Bias-correcting 1 members separately...
[2021-10-29 16:46:35] Done.
Validation 15, 7 remaining
[2021-10-29 16:46:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:36] Number of windows considered: 1...
[2021-10-29 16:46:36] Bias-correcting 1 members separately...
[2021-10-29 16:46:37] Done.
Validation 16, 6 remaining
[2021-10-29 16:46:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:38] Number of windows considered: 1...
[2021-10-29 16:46:38] Bias-correcting 1 members separately...
[2021-10-29 16:46:38] Done.
Validation 17, 5 remaining
[2021-10-29 16:46:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:39] Number of windows considered: 1...
[2021-10-29 16:46:39] Bias-correcting 1 members separately...
[2021-10-29 16:46:39] Done.
Validation 18, 4 remaining
[2021-10-29 16:46:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:40] Number of windows considered: 1...
[2021-10-29 16:46:40] Bias-correcting 1 members separately...
[2021-10-29 16:46:41] Done.
Validation 19, 3 remaining
[2021-10-29 16:46:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:42] Number of windows considered: 1...
[2021-10-29 16:46:42] Bias-correcting 1 members separately...
[2021-10-29 16:46:42] Done.
Validation 20, 2 remaining
[2021-10-29 16:46:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:43] Number of windows considered: 1...
[2021-10-29 16:46:43] Bias-correcting 1 members separately...
[2021-10-29 16:46:43] Done.
Validation 21, 1 remaining
[2021-10-29 16:46:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:44] Number of windows considered: 1...
[2021-10-29 16:46:44] Bias-correcting 1 members separately...
[2021-10-29 16:46:44] Done.
Validation 22, 0 remaining
[2021-10-29 16:46:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:45] Number of windows considered: 1...
[2021-10-29 16:46:45] Bias-correcting 1 members separately...
[2021-10-29 16:46:46] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 16:46:46] Performing annual aggregation...
[2021-10-29 16:46:46] Done.
[2021-10-29 16:46:46] - Computing climatology...
[2021-10-29 16:46:46] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.eqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", cross.val = "loo")
Validation 1, 21 remaining
[2021-10-29 16:46:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:48] Number of windows considered: 1...
[2021-10-29 16:46:48] Bias-correcting 1 members separately...
[2021-10-29 16:46:48] Done.
Validation 2, 20 remaining
[2021-10-29 16:46:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:49] Number of windows considered: 1...
[2021-10-29 16:46:49] Bias-correcting 1 members separately...
[2021-10-29 16:46:49] Done.
Validation 3, 19 remaining
[2021-10-29 16:46:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:51] Number of windows considered: 1...
[2021-10-29 16:46:51] Bias-correcting 1 members separately...
[2021-10-29 16:46:51] Done.
Validation 4, 18 remaining
[2021-10-29 16:46:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:52] Number of windows considered: 1...
[2021-10-29 16:46:52] Bias-correcting 1 members separately...
[2021-10-29 16:46:52] Done.
Validation 5, 17 remaining
[2021-10-29 16:46:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:54] Number of windows considered: 1...
[2021-10-29 16:46:54] Bias-correcting 1 members separately...
[2021-10-29 16:46:54] Done.
Validation 6, 16 remaining
[2021-10-29 16:46:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:55] Number of windows considered: 1...
[2021-10-29 16:46:55] Bias-correcting 1 members separately...
[2021-10-29 16:46:56] Done.
Validation 7, 15 remaining
[2021-10-29 16:46:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:57] Number of windows considered: 1...
[2021-10-29 16:46:57] Bias-correcting 1 members separately...
[2021-10-29 16:46:57] Done.
Validation 8, 14 remaining
[2021-10-29 16:46:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:46:59] Number of windows considered: 1...
[2021-10-29 16:46:59] Bias-correcting 1 members separately...
[2021-10-29 16:46:59] Done.
Validation 9, 13 remaining
[2021-10-29 16:47:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:00] Number of windows considered: 1...
[2021-10-29 16:47:00] Bias-correcting 1 members separately...
[2021-10-29 16:47:00] Done.
Validation 10, 12 remaining
[2021-10-29 16:47:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:02] Number of windows considered: 1...
[2021-10-29 16:47:02] Bias-correcting 1 members separately...
[2021-10-29 16:47:02] Done.
Validation 11, 11 remaining
[2021-10-29 16:47:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:03] Number of windows considered: 1...
[2021-10-29 16:47:03] Bias-correcting 1 members separately...
[2021-10-29 16:47:04] Done.
Validation 12, 10 remaining
[2021-10-29 16:47:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:05] Number of windows considered: 1...
[2021-10-29 16:47:05] Bias-correcting 1 members separately...
[2021-10-29 16:47:05] Done.
Validation 13, 9 remaining
[2021-10-29 16:47:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:06] Number of windows considered: 1...
[2021-10-29 16:47:06] Bias-correcting 1 members separately...
[2021-10-29 16:47:06] Done.
Validation 14, 8 remaining
[2021-10-29 16:47:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:08] Number of windows considered: 1...
[2021-10-29 16:47:08] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:47:08] Done.
Validation 15, 7 remaining
[2021-10-29 16:47:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:10] Number of windows considered: 1...
[2021-10-29 16:47:10] Bias-correcting 1 members separately...
[2021-10-29 16:47:10] Done.
Validation 16, 6 remaining
[2021-10-29 16:47:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:11] Number of windows considered: 1...
[2021-10-29 16:47:11] Bias-correcting 1 members separately...
[2021-10-29 16:47:12] Done.
Validation 17, 5 remaining
[2021-10-29 16:47:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:13] Number of windows considered: 1...
[2021-10-29 16:47:13] Bias-correcting 1 members separately...
[2021-10-29 16:47:13] Done.
Validation 18, 4 remaining
[2021-10-29 16:47:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:15] Number of windows considered: 1...
[2021-10-29 16:47:15] Bias-correcting 1 members separately...
[2021-10-29 16:47:15] Done.
Validation 19, 3 remaining
[2021-10-29 16:47:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:16] Number of windows considered: 1...
[2021-10-29 16:47:16] Bias-correcting 1 members separately...
[2021-10-29 16:47:17] Done.
Validation 20, 2 remaining
[2021-10-29 16:47:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:18] Number of windows considered: 1...
[2021-10-29 16:47:18] Bias-correcting 1 members separately...
[2021-10-29 16:47:19] Done.
Validation 21, 1 remaining
[2021-10-29 16:47:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:20] Number of windows considered: 1...
[2021-10-29 16:47:20] Bias-correcting 1 members separately...
[2021-10-29 16:47:20] Done.
Validation 22, 0 remaining
[2021-10-29 16:47:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:21] Number of windows considered: 1...
[2021-10-29 16:47:21] Bias-correcting 1 members separately...
[2021-10-29 16:47:22] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 16:47:22] Performing annual aggregation...
[2021-10-29 16:47:22] Done.
[2021-10-29 16:47:22] - Computing climatology...
[2021-10-29 16:47:22] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", theta = .7)
[2021-10-29 16:47:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:25] Number of windows considered: 1...
[2021-10-29 16:47:25] Bias-correcting 1 members separately...
[2021-10-29 16:47:25] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 16:47:26] Performing annual aggregation...
[2021-10-29 16:47:26] Done.
[2021-10-29 16:47:26] - Computing climatology...
[2021-10-29 16:47:26] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm2.complete <- index.cal.station.complete
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.trmm.complete[i]-index.obs.complete[i]),abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
score.trmm <- c()
for (i in c(1:9)) {
score.trmm <- c(score.trmm, norm.vector[[i]][1])
}
score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][2])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][3])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][4])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][5])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
PQM-C EQM-C GPQM-C GPQM2-C TRMM
0.7776677 0.7765603 0.7084041 0.4258728 0.2934584
scores.complete <- scores
paste(names(scores.st2.wt1[1]),names(scores.st2.wt2[1]),names(scores.st2.wt3[1]),names(scores.st2.wt4[1]),names(scores.st2.wt5[1]), names(scores.complete[1]))
[1] "PQM-WT1 EQM-WT2 GPQM-WT3 PQM-WT4 EQM-WT5 PQM-C"
Combination of techniques by WT
cal.station.cl1.pqm <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "pqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 16:47:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:28] Number of windows considered: 1...
[2021-10-29 16:47:28] Bias-correcting 1 members separately...
[2021-10-29 16:47:28] Done.
Validation 2, 20 remaining
[2021-10-29 16:47:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:29] Number of windows considered: 1...
[2021-10-29 16:47:29] Bias-correcting 1 members separately...
[2021-10-29 16:47:29] Done.
Validation 3, 19 remaining
[2021-10-29 16:47:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:31] Number of windows considered: 1...
[2021-10-29 16:47:31] Bias-correcting 1 members separately...
[2021-10-29 16:47:31] Done.
Validation 4, 18 remaining
[2021-10-29 16:47:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:32] Number of windows considered: 1...
[2021-10-29 16:47:32] Bias-correcting 1 members separately...
[2021-10-29 16:47:32] Done.
Validation 5, 17 remaining
[2021-10-29 16:47:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:33] Number of windows considered: 1...
[2021-10-29 16:47:33] Bias-correcting 1 members separately...
[2021-10-29 16:47:33] Done.
Validation 6, 16 remaining
[2021-10-29 16:47:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:34] Number of windows considered: 1...
[2021-10-29 16:47:34] Bias-correcting 1 members separately...
[2021-10-29 16:47:34] Done.
Validation 7, 15 remaining
[2021-10-29 16:47:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:35] Number of windows considered: 1...
[2021-10-29 16:47:35] Bias-correcting 1 members separately...
[2021-10-29 16:47:35] Done.
Validation 8, 14 remaining
[2021-10-29 16:47:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:36] Number of windows considered: 1...
[2021-10-29 16:47:36] Bias-correcting 1 members separately...
[2021-10-29 16:47:36] Done.
Validation 9, 13 remaining
[2021-10-29 16:47:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:37] Number of windows considered: 1...
[2021-10-29 16:47:37] Bias-correcting 1 members separately...
[2021-10-29 16:47:37] Done.
Validation 10, 12 remaining
[2021-10-29 16:47:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:39] Number of windows considered: 1...
[2021-10-29 16:47:39] Bias-correcting 1 members separately...
[2021-10-29 16:47:39] Done.
Validation 11, 11 remaining
[2021-10-29 16:47:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:40] Number of windows considered: 1...
[2021-10-29 16:47:40] Bias-correcting 1 members separately...
[2021-10-29 16:47:40] Done.
Validation 12, 10 remaining
[2021-10-29 16:47:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:41] Number of windows considered: 1...
[2021-10-29 16:47:41] Bias-correcting 1 members separately...
[2021-10-29 16:47:41] Done.
Validation 13, 9 remaining
[2021-10-29 16:47:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:42] Number of windows considered: 1...
[2021-10-29 16:47:42] Bias-correcting 1 members separately...
[2021-10-29 16:47:42] Done.
Validation 14, 8 remaining
[2021-10-29 16:47:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:43] Number of windows considered: 1...
[2021-10-29 16:47:43] Bias-correcting 1 members separately...
[2021-10-29 16:47:43] Done.
Validation 15, 7 remaining
[2021-10-29 16:47:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:45] Number of windows considered: 1...
[2021-10-29 16:47:45] Bias-correcting 1 members separately...
[2021-10-29 16:47:45] Done.
Validation 16, 6 remaining
[2021-10-29 16:47:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:47] Number of windows considered: 1...
[2021-10-29 16:47:47] Bias-correcting 1 members separately...
[2021-10-29 16:47:47] Done.
Validation 17, 5 remaining
[2021-10-29 16:47:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:48] Number of windows considered: 1...
[2021-10-29 16:47:48] Bias-correcting 1 members separately...
[2021-10-29 16:47:48] Done.
Validation 18, 4 remaining
[2021-10-29 16:47:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:49] Number of windows considered: 1...
[2021-10-29 16:47:49] Bias-correcting 1 members separately...
[2021-10-29 16:47:49] Done.
Validation 19, 3 remaining
[2021-10-29 16:47:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:50] Number of windows considered: 1...
[2021-10-29 16:47:50] Bias-correcting 1 members separately...
[2021-10-29 16:47:50] Done.
Validation 20, 2 remaining
[2021-10-29 16:47:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:51] Number of windows considered: 1...
[2021-10-29 16:47:51] Bias-correcting 1 members separately...
[2021-10-29 16:47:51] Done.
Validation 21, 1 remaining
[2021-10-29 16:47:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:52] Number of windows considered: 1...
[2021-10-29 16:47:52] Bias-correcting 1 members separately...
[2021-10-29 16:47:52] Done.
Validation 22, 0 remaining
[2021-10-29 16:47:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:53] Number of windows considered: 1...
[2021-10-29 16:47:53] Bias-correcting 1 members separately...
[2021-10-29 16:47:53] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1.pqm$Dates$start <- as.POSIXct(cal.station.cl1.pqm$Dates$start,tz = "GMT")
cal.station.cl1.pqm$Dates$end <- as.POSIXct(cal.station.cl1.pqm$Dates$end,tz = "GMT")
cal.station.cl2.eqm <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "eqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 16:47:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:55] Number of windows considered: 1...
[2021-10-29 16:47:55] Bias-correcting 1 members separately...
[2021-10-29 16:47:56] Done.
Validation 2, 20 remaining
[2021-10-29 16:47:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:57] Number of windows considered: 1...
[2021-10-29 16:47:57] Bias-correcting 1 members separately...
[2021-10-29 16:47:57] Done.
Validation 3, 19 remaining
[2021-10-29 16:47:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:47:58] Number of windows considered: 1...
[2021-10-29 16:47:58] Bias-correcting 1 members separately...
[2021-10-29 16:47:58] Done.
Validation 4, 18 remaining
[2021-10-29 16:48:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:00] Number of windows considered: 1...
[2021-10-29 16:48:00] Bias-correcting 1 members separately...
[2021-10-29 16:48:00] Done.
Validation 5, 17 remaining
[2021-10-29 16:48:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:01] Number of windows considered: 1...
[2021-10-29 16:48:01] Bias-correcting 1 members separately...
[2021-10-29 16:48:01] Done.
Validation 6, 16 remaining
[2021-10-29 16:48:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:02] Number of windows considered: 1...
[2021-10-29 16:48:02] Bias-correcting 1 members separately...
[2021-10-29 16:48:02] Done.
Validation 7, 15 remaining
[2021-10-29 16:48:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:03] Number of windows considered: 1...
[2021-10-29 16:48:03] Bias-correcting 1 members separately...
[2021-10-29 16:48:04] Done.
Validation 8, 14 remaining
[2021-10-29 16:48:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:05] Number of windows considered: 1...
[2021-10-29 16:48:05] Bias-correcting 1 members separately...
[2021-10-29 16:48:05] Done.
Validation 9, 13 remaining
[2021-10-29 16:48:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:06] Number of windows considered: 1...
[2021-10-29 16:48:06] Bias-correcting 1 members separately...
[2021-10-29 16:48:06] Done.
Validation 10, 12 remaining
[2021-10-29 16:48:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:07] Number of windows considered: 1...
[2021-10-29 16:48:07] Bias-correcting 1 members separately...
[2021-10-29 16:48:07] Done.
Validation 11, 11 remaining
[2021-10-29 16:48:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:08] Number of windows considered: 1...
[2021-10-29 16:48:08] Bias-correcting 1 members separately...
[2021-10-29 16:48:08] Done.
Validation 12, 10 remaining
[2021-10-29 16:48:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:09] Number of windows considered: 1...
[2021-10-29 16:48:09] Bias-correcting 1 members separately...
[2021-10-29 16:48:09] Done.
Validation 13, 9 remaining
[2021-10-29 16:48:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:11] Number of windows considered: 1...
[2021-10-29 16:48:11] Bias-correcting 1 members separately...
[2021-10-29 16:48:11] Done.
Validation 14, 8 remaining
[2021-10-29 16:48:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:12] Number of windows considered: 1...
[2021-10-29 16:48:12] Bias-correcting 1 members separately...
[2021-10-29 16:48:12] Done.
Validation 15, 7 remaining
[2021-10-29 16:48:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:13] Number of windows considered: 1...
[2021-10-29 16:48:13] Bias-correcting 1 members separately...
[2021-10-29 16:48:13] Done.
Validation 16, 6 remaining
[2021-10-29 16:48:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:14] Number of windows considered: 1...
[2021-10-29 16:48:14] Bias-correcting 1 members separately...
[2021-10-29 16:48:14] Done.
Validation 17, 5 remaining
[2021-10-29 16:48:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:16] Number of windows considered: 1...
[2021-10-29 16:48:16] Bias-correcting 1 members separately...
[2021-10-29 16:48:16] Done.
Validation 18, 4 remaining
[2021-10-29 16:48:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:17] Number of windows considered: 1...
[2021-10-29 16:48:17] Bias-correcting 1 members separately...
[2021-10-29 16:48:17] Done.
Validation 19, 3 remaining
[2021-10-29 16:48:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:18] Number of windows considered: 1...
[2021-10-29 16:48:18] Bias-correcting 1 members separately...
[2021-10-29 16:48:18] Done.
Validation 20, 2 remaining
[2021-10-29 16:48:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:20] Number of windows considered: 1...
[2021-10-29 16:48:20] Bias-correcting 1 members separately...
[2021-10-29 16:48:20] Done.
Validation 21, 1 remaining
[2021-10-29 16:48:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:21] Number of windows considered: 1...
[2021-10-29 16:48:21] Bias-correcting 1 members separately...
[2021-10-29 16:48:21] Done.
Validation 22, 0 remaining
[2021-10-29 16:48:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:22] Number of windows considered: 1...
[2021-10-29 16:48:22] Bias-correcting 1 members separately...
[2021-10-29 16:48:22] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2.eqm$Dates$start <- as.POSIXct(cal.station.cl2.eqm$Dates$start,tz = "GMT")
cal.station.cl2.eqm$Dates$end <- as.POSIXct(cal.station.cl2.eqm$Dates$end,tz = "GMT")
cal.station.cl3.gpqm <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 16:48:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:24] Number of windows considered: 1...
[2021-10-29 16:48:24] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 16:48:24] Done.
Validation 2, 20 remaining
[2021-10-29 16:48:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:25] Number of windows considered: 1...
[2021-10-29 16:48:25] Bias-correcting 1 members separately...
[2021-10-29 16:48:25] Done.
Validation 3, 19 remaining
[2021-10-29 16:48:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:26] Number of windows considered: 1...
[2021-10-29 16:48:26] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:48:26] Done.
Validation 4, 18 remaining
[2021-10-29 16:48:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:28] Number of windows considered: 1...
[2021-10-29 16:48:28] Bias-correcting 1 members separately...
[2021-10-29 16:48:28] Done.
Validation 5, 17 remaining
[2021-10-29 16:48:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:29] Number of windows considered: 1...
[2021-10-29 16:48:29] Bias-correcting 1 members separately...
[2021-10-29 16:48:29] Done.
Validation 6, 16 remaining
[2021-10-29 16:48:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:30] Number of windows considered: 1...
[2021-10-29 16:48:30] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:48:30] Done.
Validation 7, 15 remaining
[2021-10-29 16:48:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:31] Number of windows considered: 1...
[2021-10-29 16:48:31] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:48:31] Done.
Validation 8, 14 remaining
[2021-10-29 16:48:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:32] Number of windows considered: 1...
[2021-10-29 16:48:32] Bias-correcting 1 members separately...
[2021-10-29 16:48:33] Done.
Validation 9, 13 remaining
[2021-10-29 16:48:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:34] Number of windows considered: 1...
[2021-10-29 16:48:34] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:48:34] Done.
Validation 10, 12 remaining
[2021-10-29 16:48:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:35] Number of windows considered: 1...
[2021-10-29 16:48:35] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:48:35] Done.
Validation 11, 11 remaining
[2021-10-29 16:48:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:36] Number of windows considered: 1...
[2021-10-29 16:48:36] Bias-correcting 1 members separately...
[2021-10-29 16:48:36] Done.
Validation 12, 10 remaining
[2021-10-29 16:48:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:37] Number of windows considered: 1...
[2021-10-29 16:48:37] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:48:37] Done.
Validation 13, 9 remaining
[2021-10-29 16:48:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:38] Number of windows considered: 1...
[2021-10-29 16:48:38] Bias-correcting 1 members separately...
[2021-10-29 16:48:38] Done.
Validation 14, 8 remaining
[2021-10-29 16:48:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:39] Number of windows considered: 1...
[2021-10-29 16:48:39] Bias-correcting 1 members separately...
[2021-10-29 16:48:40] Done.
Validation 15, 7 remaining
[2021-10-29 16:48:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:41] Number of windows considered: 1...
[2021-10-29 16:48:41] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:48:41] Done.
Validation 16, 6 remaining
[2021-10-29 16:48:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:42] Number of windows considered: 1...
[2021-10-29 16:48:42] Bias-correcting 1 members separately...
[2021-10-29 16:48:42] Done.
Validation 17, 5 remaining
[2021-10-29 16:48:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:43] Number of windows considered: 1...
[2021-10-29 16:48:43] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:48:43] Done.
Validation 18, 4 remaining
[2021-10-29 16:48:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:45] Number of windows considered: 1...
[2021-10-29 16:48:45] Bias-correcting 1 members separately...
[2021-10-29 16:48:45] Done.
Validation 19, 3 remaining
[2021-10-29 16:48:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:46] Number of windows considered: 1...
[2021-10-29 16:48:46] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:48:46] Done.
Validation 20, 2 remaining
[2021-10-29 16:48:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:47] Number of windows considered: 1...
[2021-10-29 16:48:47] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 16:48:47] Done.
Validation 21, 1 remaining
[2021-10-29 16:48:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:49] Number of windows considered: 1...
[2021-10-29 16:48:49] Bias-correcting 1 members separately...
[2021-10-29 16:48:49] Done.
Validation 22, 0 remaining
[2021-10-29 16:48:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:50] Number of windows considered: 1...
[2021-10-29 16:48:50] Bias-correcting 1 members separately...
[2021-10-29 16:48:50] Done.
cal.station.cl3.gpqm$Dates$start <- as.POSIXct(cal.station.cl3.gpqm$Dates$start,tz = "GMT")
cal.station.cl3.gpqm$Dates$end <- as.POSIXct(cal.station.cl3.gpqm$Dates$end,tz = "GMT")
cal.station.cl4.eqm <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "eqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 16:48:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:52] Number of windows considered: 1...
[2021-10-29 16:48:52] Bias-correcting 1 members separately...
[2021-10-29 16:48:52] Done.
Validation 2, 20 remaining
[2021-10-29 16:48:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:53] Number of windows considered: 1...
[2021-10-29 16:48:53] Bias-correcting 1 members separately...
[2021-10-29 16:48:53] Done.
Validation 3, 19 remaining
[2021-10-29 16:48:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:54] Number of windows considered: 1...
[2021-10-29 16:48:54] Bias-correcting 1 members separately...
[2021-10-29 16:48:54] Done.
Validation 4, 18 remaining
[2021-10-29 16:48:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:56] Number of windows considered: 1...
[2021-10-29 16:48:56] Bias-correcting 1 members separately...
[2021-10-29 16:48:56] Done.
Validation 5, 17 remaining
[2021-10-29 16:48:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:57] Number of windows considered: 1...
[2021-10-29 16:48:57] Bias-correcting 1 members separately...
[2021-10-29 16:48:57] Done.
Validation 6, 16 remaining
[2021-10-29 16:48:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:48:59] Number of windows considered: 1...
[2021-10-29 16:48:59] Bias-correcting 1 members separately...
[2021-10-29 16:48:59] Done.
Validation 7, 15 remaining
[2021-10-29 16:49:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:00] Number of windows considered: 1...
[2021-10-29 16:49:00] Bias-correcting 1 members separately...
[2021-10-29 16:49:00] Done.
Validation 8, 14 remaining
[2021-10-29 16:49:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:01] Number of windows considered: 1...
[2021-10-29 16:49:01] Bias-correcting 1 members separately...
[2021-10-29 16:49:02] Done.
Validation 9, 13 remaining
[2021-10-29 16:49:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:03] Number of windows considered: 1...
[2021-10-29 16:49:03] Bias-correcting 1 members separately...
[2021-10-29 16:49:03] Done.
Validation 10, 12 remaining
[2021-10-29 16:49:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:04] Number of windows considered: 1...
[2021-10-29 16:49:04] Bias-correcting 1 members separately...
[2021-10-29 16:49:04] Done.
Validation 11, 11 remaining
[2021-10-29 16:49:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:05] Number of windows considered: 1...
[2021-10-29 16:49:05] Bias-correcting 1 members separately...
[2021-10-29 16:49:05] Done.
Validation 12, 10 remaining
[2021-10-29 16:49:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:07] Number of windows considered: 1...
[2021-10-29 16:49:07] Bias-correcting 1 members separately...
[2021-10-29 16:49:07] Done.
Validation 13, 9 remaining
[2021-10-29 16:49:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:08] Number of windows considered: 1...
[2021-10-29 16:49:08] Bias-correcting 1 members separately...
[2021-10-29 16:49:08] Done.
Validation 14, 8 remaining
[2021-10-29 16:49:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:09] Number of windows considered: 1...
[2021-10-29 16:49:09] Bias-correcting 1 members separately...
[2021-10-29 16:49:09] Done.
Validation 15, 7 remaining
[2021-10-29 16:49:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:10] Number of windows considered: 1...
[2021-10-29 16:49:10] Bias-correcting 1 members separately...
[2021-10-29 16:49:10] Done.
Validation 16, 6 remaining
[2021-10-29 16:49:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:12] Number of windows considered: 1...
[2021-10-29 16:49:12] Bias-correcting 1 members separately...
[2021-10-29 16:49:12] Done.
Validation 17, 5 remaining
[2021-10-29 16:49:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:13] Number of windows considered: 1...
[2021-10-29 16:49:13] Bias-correcting 1 members separately...
[2021-10-29 16:49:13] Done.
Validation 18, 4 remaining
[2021-10-29 16:49:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:14] Number of windows considered: 1...
[2021-10-29 16:49:14] Bias-correcting 1 members separately...
[2021-10-29 16:49:14] Done.
Validation 19, 3 remaining
[2021-10-29 16:49:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:15] Number of windows considered: 1...
[2021-10-29 16:49:15] Bias-correcting 1 members separately...
[2021-10-29 16:49:15] Done.
Validation 20, 2 remaining
[2021-10-29 16:49:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:17] Number of windows considered: 1...
[2021-10-29 16:49:17] Bias-correcting 1 members separately...
[2021-10-29 16:49:17] Done.
Validation 21, 1 remaining
[2021-10-29 16:49:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:18] Number of windows considered: 1...
[2021-10-29 16:49:18] Bias-correcting 1 members separately...
[2021-10-29 16:49:18] Done.
Validation 22, 0 remaining
[2021-10-29 16:49:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:20] Number of windows considered: 1...
[2021-10-29 16:49:20] Bias-correcting 1 members separately...
[2021-10-29 16:49:20] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4.eqm$Dates$start <- as.POSIXct(cal.station.cl4.eqm$Dates$start,tz = "GMT")
cal.station.cl4.eqm$Dates$end <- as.POSIXct(cal.station.cl4.eqm$Dates$end,tz = "GMT")
cal.station.cl5.eqm <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "eqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 16:49:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:22] Number of windows considered: 1...
[2021-10-29 16:49:22] Bias-correcting 1 members separately...
[2021-10-29 16:49:22] Done.
Validation 2, 20 remaining
[2021-10-29 16:49:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:23] Number of windows considered: 1...
[2021-10-29 16:49:23] Bias-correcting 1 members separately...
[2021-10-29 16:49:23] Done.
Validation 3, 19 remaining
[2021-10-29 16:49:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:24] Number of windows considered: 1...
[2021-10-29 16:49:24] Bias-correcting 1 members separately...
[2021-10-29 16:49:24] Done.
Validation 4, 18 remaining
[2021-10-29 16:49:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:25] Number of windows considered: 1...
[2021-10-29 16:49:25] Bias-correcting 1 members separately...
[2021-10-29 16:49:25] Done.
Validation 5, 17 remaining
[2021-10-29 16:49:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:26] Number of windows considered: 1...
[2021-10-29 16:49:26] Bias-correcting 1 members separately...
[2021-10-29 16:49:26] Done.
Validation 6, 16 remaining
[2021-10-29 16:49:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:27] Number of windows considered: 1...
[2021-10-29 16:49:27] Bias-correcting 1 members separately...
[2021-10-29 16:49:27] Done.
Validation 7, 15 remaining
[2021-10-29 16:49:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:28] Number of windows considered: 1...
[2021-10-29 16:49:28] Bias-correcting 1 members separately...
[2021-10-29 16:49:28] Done.
Validation 8, 14 remaining
[2021-10-29 16:49:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:29] Number of windows considered: 1...
[2021-10-29 16:49:29] Bias-correcting 1 members separately...
[2021-10-29 16:49:29] Done.
Validation 9, 13 remaining
[2021-10-29 16:49:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:30] Number of windows considered: 1...
[2021-10-29 16:49:30] Bias-correcting 1 members separately...
[2021-10-29 16:49:30] Done.
Validation 10, 12 remaining
[2021-10-29 16:49:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:31] Number of windows considered: 1...
[2021-10-29 16:49:31] Bias-correcting 1 members separately...
[2021-10-29 16:49:31] Done.
Validation 11, 11 remaining
[2021-10-29 16:49:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:32] Number of windows considered: 1...
[2021-10-29 16:49:32] Bias-correcting 1 members separately...
[2021-10-29 16:49:32] Done.
Validation 12, 10 remaining
[2021-10-29 16:49:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:33] Number of windows considered: 1...
[2021-10-29 16:49:33] Bias-correcting 1 members separately...
[2021-10-29 16:49:33] Done.
Validation 13, 9 remaining
[2021-10-29 16:49:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:35] Number of windows considered: 1...
[2021-10-29 16:49:35] Bias-correcting 1 members separately...
[2021-10-29 16:49:35] Done.
Validation 14, 8 remaining
[2021-10-29 16:49:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:36] Number of windows considered: 1...
[2021-10-29 16:49:36] Bias-correcting 1 members separately...
[2021-10-29 16:49:36] Done.
Validation 15, 7 remaining
[2021-10-29 16:49:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:37] Number of windows considered: 1...
[2021-10-29 16:49:37] Bias-correcting 1 members separately...
[2021-10-29 16:49:37] Done.
Validation 16, 6 remaining
[2021-10-29 16:49:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:38] Number of windows considered: 1...
[2021-10-29 16:49:38] Bias-correcting 1 members separately...
[2021-10-29 16:49:38] Done.
Validation 17, 5 remaining
[2021-10-29 16:49:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:40] Number of windows considered: 1...
[2021-10-29 16:49:40] Bias-correcting 1 members separately...
[2021-10-29 16:49:40] Done.
Validation 18, 4 remaining
[2021-10-29 16:49:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:41] Number of windows considered: 1...
[2021-10-29 16:49:41] Bias-correcting 1 members separately...
[2021-10-29 16:49:41] Done.
Validation 19, 3 remaining
[2021-10-29 16:49:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:42] Number of windows considered: 1...
[2021-10-29 16:49:42] Bias-correcting 1 members separately...
[2021-10-29 16:49:42] Done.
Validation 20, 2 remaining
[2021-10-29 16:49:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:43] Number of windows considered: 1...
[2021-10-29 16:49:43] Bias-correcting 1 members separately...
[2021-10-29 16:49:44] Done.
Validation 21, 1 remaining
[2021-10-29 16:49:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:45] Number of windows considered: 1...
[2021-10-29 16:49:45] Bias-correcting 1 members separately...
[2021-10-29 16:49:45] Done.
Validation 22, 0 remaining
[2021-10-29 16:49:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:46] Number of windows considered: 1...
[2021-10-29 16:49:46] Bias-correcting 1 members separately...
[2021-10-29 16:49:46] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5.eqm$Dates$start <- as.POSIXct(cal.station.cl5.eqm$Dates$start,tz = "GMT")
cal.station.cl5.eqm$Dates$end <- as.POSIXct(cal.station.cl5.eqm$Dates$end,tz = "GMT")
idx <- which(!is.na(cal.station.cl1.pqm$Data))
cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl2.eqm$Data))
cal.station.cl2.eqm <- subsetDimension(cal.station.cl2.eqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl3.gpqm$Data))
cal.station.cl3.gpqm <- subsetDimension(cal.station.cl3.gpqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl4.eqm$Data))
cal.station.cl4.eqm <- subsetDimension(cal.station.cl4.eqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl5.eqm$Data))
cal.station.cl5.eqm <- subsetDimension(cal.station.cl5.eqm, dimension = "time", indices = idx)
wt_conditioned <- bindGrid(cal.station.cl1.pqm, cal.station.cl2.eqm, cal.station.cl3.gpqm,
cal.station.cl4.eqm, cal.station.cl5.eqm, dimension = "time")
attr(wt_conditioned$Data, "dimensions") <- "time"
#cambiar de tipo de biasCorrection y fillGridDates
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "pqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-10-29 16:49:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:49] Number of windows considered: 1...
[2021-10-29 16:49:49] Bias-correcting 1 members separately...
[2021-10-29 16:49:49] Done.
Validation 2, 20 remaining
[2021-10-29 16:49:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:50] Number of windows considered: 1...
[2021-10-29 16:49:50] Bias-correcting 1 members separately...
[2021-10-29 16:49:50] Done.
Validation 3, 19 remaining
[2021-10-29 16:49:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:52] Number of windows considered: 1...
[2021-10-29 16:49:52] Bias-correcting 1 members separately...
[2021-10-29 16:49:52] Done.
Validation 4, 18 remaining
[2021-10-29 16:49:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:53] Number of windows considered: 1...
[2021-10-29 16:49:53] Bias-correcting 1 members separately...
[2021-10-29 16:49:53] Done.
Validation 5, 17 remaining
[2021-10-29 16:49:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:54] Number of windows considered: 1...
[2021-10-29 16:49:54] Bias-correcting 1 members separately...
[2021-10-29 16:49:54] Done.
Validation 6, 16 remaining
[2021-10-29 16:49:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:56] Number of windows considered: 1...
[2021-10-29 16:49:56] Bias-correcting 1 members separately...
[2021-10-29 16:49:56] Done.
Validation 7, 15 remaining
[2021-10-29 16:49:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:57] Number of windows considered: 1...
[2021-10-29 16:49:57] Bias-correcting 1 members separately...
[2021-10-29 16:49:57] Done.
Validation 8, 14 remaining
[2021-10-29 16:49:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:49:59] Number of windows considered: 1...
[2021-10-29 16:49:59] Bias-correcting 1 members separately...
[2021-10-29 16:49:59] Done.
Validation 9, 13 remaining
[2021-10-29 16:50:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:00] Number of windows considered: 1...
[2021-10-29 16:50:00] Bias-correcting 1 members separately...
[2021-10-29 16:50:01] Done.
Validation 10, 12 remaining
[2021-10-29 16:50:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:02] Number of windows considered: 1...
[2021-10-29 16:50:02] Bias-correcting 1 members separately...
[2021-10-29 16:50:02] Done.
Validation 11, 11 remaining
[2021-10-29 16:50:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:03] Number of windows considered: 1...
[2021-10-29 16:50:03] Bias-correcting 1 members separately...
[2021-10-29 16:50:03] Done.
Validation 12, 10 remaining
[2021-10-29 16:50:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:04] Number of windows considered: 1...
[2021-10-29 16:50:04] Bias-correcting 1 members separately...
[2021-10-29 16:50:04] Done.
Validation 13, 9 remaining
[2021-10-29 16:50:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:06] Number of windows considered: 1...
[2021-10-29 16:50:06] Bias-correcting 1 members separately...
[2021-10-29 16:50:06] Done.
Validation 14, 8 remaining
[2021-10-29 16:50:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:07] Number of windows considered: 1...
[2021-10-29 16:50:07] Bias-correcting 1 members separately...
[2021-10-29 16:50:07] Done.
Validation 15, 7 remaining
[2021-10-29 16:50:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:09] Number of windows considered: 1...
[2021-10-29 16:50:09] Bias-correcting 1 members separately...
[2021-10-29 16:50:09] Done.
Validation 16, 6 remaining
[2021-10-29 16:50:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:10] Number of windows considered: 1...
[2021-10-29 16:50:10] Bias-correcting 1 members separately...
[2021-10-29 16:50:10] Done.
Validation 17, 5 remaining
[2021-10-29 16:50:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:11] Number of windows considered: 1...
[2021-10-29 16:50:11] Bias-correcting 1 members separately...
[2021-10-29 16:50:11] Done.
Validation 18, 4 remaining
[2021-10-29 16:50:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:13] Number of windows considered: 1...
[2021-10-29 16:50:13] Bias-correcting 1 members separately...
[2021-10-29 16:50:13] Done.
Validation 19, 3 remaining
[2021-10-29 16:50:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:14] Number of windows considered: 1...
[2021-10-29 16:50:14] Bias-correcting 1 members separately...
[2021-10-29 16:50:14] Done.
Validation 20, 2 remaining
[2021-10-29 16:50:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:16] Number of windows considered: 1...
[2021-10-29 16:50:16] Bias-correcting 1 members separately...
[2021-10-29 16:50:16] Done.
Validation 21, 1 remaining
[2021-10-29 16:50:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:17] Number of windows considered: 1...
[2021-10-29 16:50:17] Bias-correcting 1 members separately...
[2021-10-29 16:50:17] Done.
Validation 22, 0 remaining
[2021-10-29 16:50:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 16:50:18] Number of windows considered: 1...
[2021-10-29 16:50:18] Bias-correcting 1 members separately...
[2021-10-29 16:50:18] Done.
# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))
index.combinated.rv20max <- MaxReturnValue(wt_conditioned)
[2021-10-29 16:50:19] Performing annual aggregation...
[2021-10-29 16:50:19] Done.
[2021-10-29 16:50:19] - Computing climatology...
[2021-10-29 16:50:19] - Done.
index.combinated <- c(index.combinated, index.combinated.rv20max)
index.pqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.pqm <- c(index.pqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.pqm.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 16:50:20] Performing annual aggregation...
[2021-10-29 16:50:20] Done.
[2021-10-29 16:50:20] - Computing climatology...
[2021-10-29 16:50:20] - Done.
index.pqm<- c(index.pqm ,index.pqm.rv20max)
index.pqm
Skewness SDII R10 R10p R20 R20p P98Wet
5.318725e+00 1.427469e+01 1.387852e-01 3.683698e+04 7.692308e-02 2.985053e+04 8.722800e+01
P98WetAmount RV20_max
8.247586e+03 1.867902e+02
diff.conditioned <- abs(index.obs-index.combinated)
diff.pqm <- abs(index.obs-index.pqm)
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
score.combinated <- c()
for (i in c(1:9)) {
score.combinated <- c(score.combinated, norm.vector[[i]][5])
}
score.combinated <- mean(score.combinated)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
Combined PQM-C EQM-C GPQM-C GPQM2-C
0.7688532 0.6010423 0.5937759 0.5264270 0.2038478
df <- data.frame(index.obs, index.combinated, index.eqm)
colnames(df) <- c("Observation","Conditioned", "PQM")
format(df, digits = 3, scientific = 5)
bias.df <- data.frame(diff.conditioned, diff.eqm)
colnames(bias.df) <- c("Bias Conditioned", "Bias PQM")
format(bias.df, digits = 3, scientific = 5)
df.st1 <- df
bias.df.st1 <- bias.df
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100
names(bias.rel.cond) <- names(diff.conditioned)
bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100
names(bias.rel.no.cond) <- names(diff.conditioned)
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)
colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias PQM")
format(bias.rel.df, digits = 3, scientific = 5)
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))
abline(a = 0, b = 1)
station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))
points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))
idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))
station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)
points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)
legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))
grid()

Rarotonga, Cook Islands
i=3
station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
[2021-11-02 09:34:21] Performing annual aggregation...
no non-missing arguments to max; returning -Inf[2021-11-02 09:34:21] Done.
[2021-11-02 09:34:21] - Computing climatology...
[2021-11-02 09:34:21] - Done.
index.obs <- c(index.obs, index.obs.rv20max)
index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
[2021-11-02 09:34:21] Performing annual aggregation...
[2021-11-02 09:34:21] Done.
[2021-11-02 09:34:21] - Computing climatology...
[2021-11-02 09:34:21] - Done.
index.trmm <- c(index.trmm, index.trmm.rv20max)
WT1
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))
station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
[2021-11-02 09:34:49] Performing annual aggregation...
no non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Inf[2021-11-02 09:34:49] Done.
[2021-11-02 09:34:49] - Computing climatology...
[2021-11-02 09:34:49] - Done.
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)
index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
[2021-11-02 09:34:49] Performing annual aggregation...
[2021-11-02 09:34:49] Done.
[2021-11-02 09:34:49] - Computing climatology...
[2021-11-02 09:34:49] - Done.
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")
station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "pqm",cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:34:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:34:53] Number of windows considered: 1...
[2021-11-02 09:34:53] Bias-correcting 1 members separately...
[2021-11-02 09:34:53] Done.
Validation 2, 20 remaining
[2021-11-02 09:34:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:34:54] Number of windows considered: 1...
[2021-11-02 09:34:54] Bias-correcting 1 members separately...
[2021-11-02 09:34:54] Done.
Validation 3, 19 remaining
[2021-11-02 09:34:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:34:55] Number of windows considered: 1...
[2021-11-02 09:34:55] Bias-correcting 1 members separately...
[2021-11-02 09:34:55] Done.
Validation 4, 18 remaining
[2021-11-02 09:34:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:34:56] Number of windows considered: 1...
[2021-11-02 09:34:56] Bias-correcting 1 members separately...
[2021-11-02 09:34:56] Done.
Validation 5, 17 remaining
[2021-11-02 09:34:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:34:57] Number of windows considered: 1...
[2021-11-02 09:34:57] Bias-correcting 1 members separately...
[2021-11-02 09:34:57] Done.
Validation 6, 16 remaining
[2021-11-02 09:34:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:34:57] Number of windows considered: 1...
[2021-11-02 09:34:57] Bias-correcting 1 members separately...
[2021-11-02 09:34:57] Done.
Validation 7, 15 remaining
[2021-11-02 09:34:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:34:58] Number of windows considered: 1...
[2021-11-02 09:34:58] Bias-correcting 1 members separately...
[2021-11-02 09:34:58] Done.
Validation 8, 14 remaining
[2021-11-02 09:34:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:34:59] Number of windows considered: 1...
[2021-11-02 09:34:59] Bias-correcting 1 members separately...
[2021-11-02 09:34:59] Done.
Validation 9, 13 remaining
[2021-11-02 09:34:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:34:59] Number of windows considered: 1...
[2021-11-02 09:34:59] Bias-correcting 1 members separately...
[2021-11-02 09:34:59] Done.
Validation 10, 12 remaining
[2021-11-02 09:35:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:35:00] Number of windows considered: 1...
[2021-11-02 09:35:00] Bias-correcting 1 members separately...
[2021-11-02 09:35:00] Done.
Validation 11, 11 remaining
[2021-11-02 09:35:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:35:01] Number of windows considered: 1...
[2021-11-02 09:35:01] Bias-correcting 1 members separately...
[2021-11-02 09:35:01] Done.
Validation 12, 10 remaining
[2021-11-02 09:35:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:35:01] Number of windows considered: 1...
[2021-11-02 09:35:01] Bias-correcting 1 members separately...
[2021-11-02 09:35:01] Done.
Validation 13, 9 remaining
[2021-11-02 09:35:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:35:02] Number of windows considered: 1...
[2021-11-02 09:35:02] Bias-correcting 1 members separately...
[2021-11-02 09:35:02] Done.
Validation 14, 8 remaining
[2021-11-02 09:35:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:35:03] Number of windows considered: 1...
[2021-11-02 09:35:03] Bias-correcting 1 members separately...
[2021-11-02 09:35:03] Done.
Validation 15, 7 remaining
[2021-11-02 09:35:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:35:03] Number of windows considered: 1...
[2021-11-02 09:35:03] Bias-correcting 1 members separately...
[2021-11-02 09:35:03] Done.
Validation 16, 6 remaining
[2021-11-02 09:35:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:35:04] Number of windows considered: 1...
[2021-11-02 09:35:04] Bias-correcting 1 members separately...
[2021-11-02 09:35:04] Done.
Validation 17, 5 remaining
[2021-11-02 09:35:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:35:05] Number of windows considered: 1...
[2021-11-02 09:35:05] Bias-correcting 1 members separately...
[2021-11-02 09:35:05] Done.
Validation 18, 4 remaining
[2021-11-02 09:35:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:35:05] Number of windows considered: 1...
[2021-11-02 09:35:05] Bias-correcting 1 members separately...
[2021-11-02 09:35:05] Done.
Validation 19, 3 remaining
[2021-11-02 09:35:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:35:06] Number of windows considered: 1...
[2021-11-02 09:35:06] Bias-correcting 1 members separately...
[2021-11-02 09:35:06] Done.
Validation 20, 2 remaining
[2021-11-02 09:35:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:35:07] Number of windows considered: 1...
[2021-11-02 09:35:07] Bias-correcting 1 members separately...
[2021-11-02 09:35:07] Done.
Validation 21, 1 remaining
[2021-11-02 09:35:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:35:07] Number of windows considered: 1...
[2021-11-02 09:35:07] Bias-correcting 1 members separately...
[2021-11-02 09:35:07] Done.
Validation 22, 0 remaining
[2021-11-02 09:35:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:35:08] Number of windows considered: 1...
[2021-11-02 09:35:08] Bias-correcting 1 members separately...
[2021-11-02 09:35:08] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-11-02 09:35:09] Performing annual aggregation...
[2021-11-02 09:35:09] Done.
[2021-11-02 09:35:09] - Computing climatology...
[2021-11-02 09:35:09] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.pqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:36:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:12] Number of windows considered: 1...
[2021-11-02 09:36:12] Bias-correcting 1 members separately...
[2021-11-02 09:36:12] Done.
Validation 2, 20 remaining
[2021-11-02 09:36:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:13] Number of windows considered: 1...
[2021-11-02 09:36:13] Bias-correcting 1 members separately...
[2021-11-02 09:36:13] Done.
Validation 3, 19 remaining
[2021-11-02 09:36:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:14] Number of windows considered: 1...
[2021-11-02 09:36:14] Bias-correcting 1 members separately...
[2021-11-02 09:36:14] Done.
Validation 4, 18 remaining
[2021-11-02 09:36:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:15] Number of windows considered: 1...
[2021-11-02 09:36:15] Bias-correcting 1 members separately...
[2021-11-02 09:36:15] Done.
Validation 5, 17 remaining
[2021-11-02 09:36:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:15] Number of windows considered: 1...
[2021-11-02 09:36:15] Bias-correcting 1 members separately...
[2021-11-02 09:36:15] Done.
Validation 6, 16 remaining
[2021-11-02 09:36:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:16] Number of windows considered: 1...
[2021-11-02 09:36:16] Bias-correcting 1 members separately...
[2021-11-02 09:36:16] Done.
Validation 7, 15 remaining
[2021-11-02 09:36:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:17] Number of windows considered: 1...
[2021-11-02 09:36:17] Bias-correcting 1 members separately...
[2021-11-02 09:36:17] Done.
Validation 8, 14 remaining
[2021-11-02 09:36:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:18] Number of windows considered: 1...
[2021-11-02 09:36:18] Bias-correcting 1 members separately...
[2021-11-02 09:36:18] Done.
Validation 9, 13 remaining
[2021-11-02 09:36:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:19] Number of windows considered: 1...
[2021-11-02 09:36:19] Bias-correcting 1 members separately...
[2021-11-02 09:36:19] Done.
Validation 10, 12 remaining
[2021-11-02 09:36:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:20] Number of windows considered: 1...
[2021-11-02 09:36:20] Bias-correcting 1 members separately...
[2021-11-02 09:36:20] Done.
Validation 11, 11 remaining
[2021-11-02 09:36:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:20] Number of windows considered: 1...
[2021-11-02 09:36:20] Bias-correcting 1 members separately...
[2021-11-02 09:36:20] Done.
Validation 12, 10 remaining
[2021-11-02 09:36:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:21] Number of windows considered: 1...
[2021-11-02 09:36:21] Bias-correcting 1 members separately...
[2021-11-02 09:36:21] Done.
Validation 13, 9 remaining
[2021-11-02 09:36:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:22] Number of windows considered: 1...
[2021-11-02 09:36:22] Bias-correcting 1 members separately...
[2021-11-02 09:36:22] Done.
Validation 14, 8 remaining
[2021-11-02 09:36:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:23] Number of windows considered: 1...
[2021-11-02 09:36:23] Bias-correcting 1 members separately...
[2021-11-02 09:36:23] Done.
Validation 15, 7 remaining
[2021-11-02 09:36:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:24] Number of windows considered: 1...
[2021-11-02 09:36:24] Bias-correcting 1 members separately...
[2021-11-02 09:36:24] Done.
Validation 16, 6 remaining
[2021-11-02 09:36:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:25] Number of windows considered: 1...
[2021-11-02 09:36:25] Bias-correcting 1 members separately...
[2021-11-02 09:36:25] Done.
Validation 17, 5 remaining
[2021-11-02 09:36:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:25] Number of windows considered: 1...
[2021-11-02 09:36:25] Bias-correcting 1 members separately...
[2021-11-02 09:36:25] Done.
Validation 18, 4 remaining
[2021-11-02 09:36:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:26] Number of windows considered: 1...
[2021-11-02 09:36:26] Bias-correcting 1 members separately...
[2021-11-02 09:36:26] Done.
Validation 19, 3 remaining
[2021-11-02 09:36:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:27] Number of windows considered: 1...
[2021-11-02 09:36:27] Bias-correcting 1 members separately...
[2021-11-02 09:36:27] Done.
Validation 20, 2 remaining
[2021-11-02 09:36:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:27] Number of windows considered: 1...
[2021-11-02 09:36:27] Bias-correcting 1 members separately...
[2021-11-02 09:36:27] Done.
Validation 21, 1 remaining
[2021-11-02 09:36:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:28] Number of windows considered: 1...
[2021-11-02 09:36:28] Bias-correcting 1 members separately...
[2021-11-02 09:36:28] Done.
Validation 22, 0 remaining
[2021-11-02 09:36:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:36:29] Number of windows considered: 1...
[2021-11-02 09:36:29] Bias-correcting 1 members separately...
[2021-11-02 09:36:29] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-11-02 09:36:29] Performing annual aggregation...
[2021-11-02 09:36:29] Done.
[2021-11-02 09:36:29] - Computing climatology...
[2021-11-02 09:36:29] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.eqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:37:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:16] Number of windows considered: 1...
[2021-11-02 09:37:16] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:37:16] Done.
Validation 2, 20 remaining
[2021-11-02 09:37:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:17] Number of windows considered: 1...
[2021-11-02 09:37:17] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:37:17] Done.
Validation 3, 19 remaining
[2021-11-02 09:37:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:18] Number of windows considered: 1...
[2021-11-02 09:37:18] Bias-correcting 1 members separately...
[2021-11-02 09:37:18] Done.
Validation 4, 18 remaining
[2021-11-02 09:37:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:18] Number of windows considered: 1...
[2021-11-02 09:37:18] Bias-correcting 1 members separately...
[2021-11-02 09:37:19] Done.
Validation 5, 17 remaining
[2021-11-02 09:37:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:19] Number of windows considered: 1...
[2021-11-02 09:37:19] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:37:19] Done.
Validation 6, 16 remaining
[2021-11-02 09:37:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:20] Number of windows considered: 1...
[2021-11-02 09:37:20] Bias-correcting 1 members separately...
[2021-11-02 09:37:20] Done.
Validation 7, 15 remaining
[2021-11-02 09:37:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:21] Number of windows considered: 1...
[2021-11-02 09:37:21] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:37:21] Done.
Validation 8, 14 remaining
[2021-11-02 09:37:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:21] Number of windows considered: 1...
[2021-11-02 09:37:21] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:37:22] Done.
Validation 9, 13 remaining
[2021-11-02 09:37:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:22] Number of windows considered: 1...
[2021-11-02 09:37:22] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:37:22] Done.
Validation 10, 12 remaining
[2021-11-02 09:37:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:23] Number of windows considered: 1...
[2021-11-02 09:37:23] Bias-correcting 1 members separately...
[2021-11-02 09:37:23] Done.
Validation 11, 11 remaining
[2021-11-02 09:37:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:24] Number of windows considered: 1...
[2021-11-02 09:37:24] Bias-correcting 1 members separately...
[2021-11-02 09:37:24] Done.
Validation 12, 10 remaining
[2021-11-02 09:37:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:25] Number of windows considered: 1...
[2021-11-02 09:37:25] Bias-correcting 1 members separately...
[2021-11-02 09:37:25] Done.
Validation 13, 9 remaining
[2021-11-02 09:37:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:25] Number of windows considered: 1...
[2021-11-02 09:37:25] Bias-correcting 1 members separately...
[2021-11-02 09:37:25] Done.
Validation 14, 8 remaining
[2021-11-02 09:37:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:26] Number of windows considered: 1...
[2021-11-02 09:37:26] Bias-correcting 1 members separately...
[2021-11-02 09:37:26] Done.
Validation 15, 7 remaining
[2021-11-02 09:37:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:27] Number of windows considered: 1...
[2021-11-02 09:37:27] Bias-correcting 1 members separately...
[2021-11-02 09:37:27] Done.
Validation 16, 6 remaining
[2021-11-02 09:37:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:28] Number of windows considered: 1...
[2021-11-02 09:37:28] Bias-correcting 1 members separately...
[2021-11-02 09:37:28] Done.
Validation 17, 5 remaining
[2021-11-02 09:37:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:28] Number of windows considered: 1...
[2021-11-02 09:37:28] Bias-correcting 1 members separately...
[2021-11-02 09:37:28] Done.
Validation 18, 4 remaining
[2021-11-02 09:37:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:29] Number of windows considered: 1...
[2021-11-02 09:37:29] Bias-correcting 1 members separately...
[2021-11-02 09:37:29] Done.
Validation 19, 3 remaining
[2021-11-02 09:37:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:30] Number of windows considered: 1...
[2021-11-02 09:37:30] Bias-correcting 1 members separately...
[2021-11-02 09:37:30] Done.
Validation 20, 2 remaining
[2021-11-02 09:37:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:31] Number of windows considered: 1...
[2021-11-02 09:37:31] Bias-correcting 1 members separately...
[2021-11-02 09:37:31] Done.
Validation 21, 1 remaining
[2021-11-02 09:37:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:32] Number of windows considered: 1...
[2021-11-02 09:37:32] Bias-correcting 1 members separately...
[2021-11-02 09:37:32] Done.
Validation 22, 0 remaining
[2021-11-02 09:37:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:37:32] Number of windows considered: 1...
[2021-11-02 09:37:32] Bias-correcting 1 members separately...
[2021-11-02 09:37:32] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-11-02 09:37:33] Performing annual aggregation...
[2021-11-02 09:37:33] Done.
[2021-11-02 09:37:33] - Computing climatology...
[2021-11-02 09:37:33] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:38:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:11] Number of windows considered: 1...
[2021-11-02 09:38:11] Bias-correcting 1 members separately...
[2021-11-02 09:38:12] Done.
Validation 2, 20 remaining
[2021-11-02 09:38:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:12] Number of windows considered: 1...
[2021-11-02 09:38:12] Bias-correcting 1 members separately...
[2021-11-02 09:38:12] Done.
Validation 3, 19 remaining
[2021-11-02 09:38:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:13] Number of windows considered: 1...
[2021-11-02 09:38:13] Bias-correcting 1 members separately...
[2021-11-02 09:38:13] Done.
Validation 4, 18 remaining
[2021-11-02 09:38:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:14] Number of windows considered: 1...
[2021-11-02 09:38:14] Bias-correcting 1 members separately...
[2021-11-02 09:38:14] Done.
Validation 5, 17 remaining
[2021-11-02 09:38:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:15] Number of windows considered: 1...
[2021-11-02 09:38:15] Bias-correcting 1 members separately...
[2021-11-02 09:38:15] Done.
Validation 6, 16 remaining
[2021-11-02 09:38:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:16] Number of windows considered: 1...
[2021-11-02 09:38:16] Bias-correcting 1 members separately...
[2021-11-02 09:38:16] Done.
Validation 7, 15 remaining
[2021-11-02 09:38:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:16] Number of windows considered: 1...
[2021-11-02 09:38:16] Bias-correcting 1 members separately...
[2021-11-02 09:38:16] Done.
Validation 8, 14 remaining
[2021-11-02 09:38:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:17] Number of windows considered: 1...
[2021-11-02 09:38:17] Bias-correcting 1 members separately...
[2021-11-02 09:38:17] Done.
Validation 9, 13 remaining
[2021-11-02 09:38:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:18] Number of windows considered: 1...
[2021-11-02 09:38:18] Bias-correcting 1 members separately...
[2021-11-02 09:38:18] Done.
Validation 10, 12 remaining
[2021-11-02 09:38:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:19] Number of windows considered: 1...
[2021-11-02 09:38:19] Bias-correcting 1 members separately...
[2021-11-02 09:38:19] Done.
Validation 11, 11 remaining
[2021-11-02 09:38:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:20] Number of windows considered: 1...
[2021-11-02 09:38:20] Bias-correcting 1 members separately...
[2021-11-02 09:38:20] Done.
Validation 12, 10 remaining
[2021-11-02 09:38:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:20] Number of windows considered: 1...
[2021-11-02 09:38:20] Bias-correcting 1 members separately...
[2021-11-02 09:38:21] Done.
Validation 13, 9 remaining
[2021-11-02 09:38:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:21] Number of windows considered: 1...
[2021-11-02 09:38:21] Bias-correcting 1 members separately...
[2021-11-02 09:38:21] Done.
Validation 14, 8 remaining
[2021-11-02 09:38:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:22] Number of windows considered: 1...
[2021-11-02 09:38:22] Bias-correcting 1 members separately...
[2021-11-02 09:38:22] Done.
Validation 15, 7 remaining
[2021-11-02 09:38:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:23] Number of windows considered: 1...
[2021-11-02 09:38:23] Bias-correcting 1 members separately...
[2021-11-02 09:38:23] Done.
Validation 16, 6 remaining
[2021-11-02 09:38:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:24] Number of windows considered: 1...
[2021-11-02 09:38:24] Bias-correcting 1 members separately...
[2021-11-02 09:38:24] Done.
Validation 17, 5 remaining
[2021-11-02 09:38:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:25] Number of windows considered: 1...
[2021-11-02 09:38:25] Bias-correcting 1 members separately...
[2021-11-02 09:38:25] Done.
Validation 18, 4 remaining
[2021-11-02 09:38:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:25] Number of windows considered: 1...
[2021-11-02 09:38:25] Bias-correcting 1 members separately...
[2021-11-02 09:38:26] Done.
Validation 19, 3 remaining
[2021-11-02 09:38:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:26] Number of windows considered: 1...
[2021-11-02 09:38:26] Bias-correcting 1 members separately...
[2021-11-02 09:38:26] Done.
Validation 20, 2 remaining
[2021-11-02 09:38:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:27] Number of windows considered: 1...
[2021-11-02 09:38:27] Bias-correcting 1 members separately...
[2021-11-02 09:38:27] Done.
Validation 21, 1 remaining
[2021-11-02 09:38:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:28] Number of windows considered: 1...
[2021-11-02 09:38:28] Bias-correcting 1 members separately...
[2021-11-02 09:38:28] Done.
Validation 22, 0 remaining
[2021-11-02 09:38:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:29] Number of windows considered: 1...
[2021-11-02 09:38:29] Bias-correcting 1 members separately...
[2021-11-02 09:38:29] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-11-02 09:38:29] Performing annual aggregation...
[2021-11-02 09:38:29] Done.
[2021-11-02 09:38:29] - Computing climatology...
[2021-11-02 09:38:29] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm2.cl1 <- index.cal.station.cl1
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i]))
}
normalization <- function(measure){
measure.norm <- c()
#measure must be a vector with the value of a certain measure of different calibrations
for (i in c(1:length(measure))) {
measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
}
return(measure.norm)
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
scores.st3.wt1 <- scores
WT2
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))
station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
[2021-11-02 09:38:48] Performing annual aggregation...
no non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Inf[2021-11-02 09:38:48] Done.
[2021-11-02 09:38:49] - Computing climatology...
[2021-11-02 09:38:49] - Done.
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)
index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
[2021-11-02 09:38:49] Performing annual aggregation...
[2021-11-02 09:38:49] Done.
[2021-11-02 09:38:49] - Computing climatology...
[2021-11-02 09:38:49] - Done.
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")
station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:38:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:53] Number of windows considered: 1...
[2021-11-02 09:38:53] Bias-correcting 1 members separately...
[2021-11-02 09:38:53] Done.
Validation 2, 20 remaining
[2021-11-02 09:38:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:53] Number of windows considered: 1...
[2021-11-02 09:38:53] Bias-correcting 1 members separately...
[2021-11-02 09:38:53] Done.
Validation 3, 19 remaining
[2021-11-02 09:38:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:54] Number of windows considered: 1...
[2021-11-02 09:38:54] Bias-correcting 1 members separately...
[2021-11-02 09:38:54] Done.
Validation 4, 18 remaining
[2021-11-02 09:38:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:54] Number of windows considered: 1...
[2021-11-02 09:38:54] Bias-correcting 1 members separately...
[2021-11-02 09:38:54] Done.
Validation 5, 17 remaining
[2021-11-02 09:38:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:55] Number of windows considered: 1...
[2021-11-02 09:38:55] Bias-correcting 1 members separately...
[2021-11-02 09:38:55] Done.
Validation 6, 16 remaining
[2021-11-02 09:38:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:56] Number of windows considered: 1...
[2021-11-02 09:38:56] Bias-correcting 1 members separately...
[2021-11-02 09:38:56] Done.
Validation 7, 15 remaining
[2021-11-02 09:38:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:56] Number of windows considered: 1...
[2021-11-02 09:38:56] Bias-correcting 1 members separately...
[2021-11-02 09:38:56] Done.
Validation 8, 14 remaining
[2021-11-02 09:38:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:57] Number of windows considered: 1...
[2021-11-02 09:38:57] Bias-correcting 1 members separately...
[2021-11-02 09:38:57] Done.
Validation 9, 13 remaining
[2021-11-02 09:38:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:58] Number of windows considered: 1...
[2021-11-02 09:38:58] Bias-correcting 1 members separately...
[2021-11-02 09:38:58] Done.
Validation 10, 12 remaining
[2021-11-02 09:38:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:58] Number of windows considered: 1...
[2021-11-02 09:38:58] Bias-correcting 1 members separately...
[2021-11-02 09:38:58] Done.
Validation 11, 11 remaining
[2021-11-02 09:38:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:38:59] Number of windows considered: 1...
[2021-11-02 09:38:59] Bias-correcting 1 members separately...
[2021-11-02 09:38:59] Done.
Validation 12, 10 remaining
[2021-11-02 09:39:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:00] Number of windows considered: 1...
[2021-11-02 09:39:00] Bias-correcting 1 members separately...
[2021-11-02 09:39:00] Done.
Validation 13, 9 remaining
[2021-11-02 09:39:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:00] Number of windows considered: 1...
[2021-11-02 09:39:00] Bias-correcting 1 members separately...
[2021-11-02 09:39:00] Done.
Validation 14, 8 remaining
[2021-11-02 09:39:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:01] Number of windows considered: 1...
[2021-11-02 09:39:01] Bias-correcting 1 members separately...
[2021-11-02 09:39:01] Done.
Validation 15, 7 remaining
[2021-11-02 09:39:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:02] Number of windows considered: 1...
[2021-11-02 09:39:02] Bias-correcting 1 members separately...
[2021-11-02 09:39:02] Done.
Validation 16, 6 remaining
[2021-11-02 09:39:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:02] Number of windows considered: 1...
[2021-11-02 09:39:02] Bias-correcting 1 members separately...
[2021-11-02 09:39:02] Done.
Validation 17, 5 remaining
[2021-11-02 09:39:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:03] Number of windows considered: 1...
[2021-11-02 09:39:03] Bias-correcting 1 members separately...
[2021-11-02 09:39:03] Done.
Validation 18, 4 remaining
[2021-11-02 09:39:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:04] Number of windows considered: 1...
[2021-11-02 09:39:04] Bias-correcting 1 members separately...
[2021-11-02 09:39:04] Done.
Validation 19, 3 remaining
[2021-11-02 09:39:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:04] Number of windows considered: 1...
[2021-11-02 09:39:04] Bias-correcting 1 members separately...
[2021-11-02 09:39:04] Done.
Validation 20, 2 remaining
[2021-11-02 09:39:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:05] Number of windows considered: 1...
[2021-11-02 09:39:05] Bias-correcting 1 members separately...
[2021-11-02 09:39:05] Done.
Validation 21, 1 remaining
[2021-11-02 09:39:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:06] Number of windows considered: 1...
[2021-11-02 09:39:06] Bias-correcting 1 members separately...
[2021-11-02 09:39:06] Done.
Validation 22, 0 remaining
[2021-11-02 09:39:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:07] Number of windows considered: 1...
[2021-11-02 09:39:07] Bias-correcting 1 members separately...
[2021-11-02 09:39:07] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-11-02 09:39:07] Performing annual aggregation...
[2021-11-02 09:39:07] Done.
[2021-11-02 09:39:07] - Computing climatology...
[2021-11-02 09:39:07] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.pqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:39:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:15] Number of windows considered: 1...
[2021-11-02 09:39:15] Bias-correcting 1 members separately...
[2021-11-02 09:39:16] Done.
Validation 2, 20 remaining
[2021-11-02 09:39:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:16] Number of windows considered: 1...
[2021-11-02 09:39:16] Bias-correcting 1 members separately...
[2021-11-02 09:39:16] Done.
Validation 3, 19 remaining
[2021-11-02 09:39:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:17] Number of windows considered: 1...
[2021-11-02 09:39:17] Bias-correcting 1 members separately...
[2021-11-02 09:39:17] Done.
Validation 4, 18 remaining
[2021-11-02 09:39:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:18] Number of windows considered: 1...
[2021-11-02 09:39:18] Bias-correcting 1 members separately...
[2021-11-02 09:39:18] Done.
Validation 5, 17 remaining
[2021-11-02 09:39:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:19] Number of windows considered: 1...
[2021-11-02 09:39:19] Bias-correcting 1 members separately...
[2021-11-02 09:39:19] Done.
Validation 6, 16 remaining
[2021-11-02 09:39:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:20] Number of windows considered: 1...
[2021-11-02 09:39:20] Bias-correcting 1 members separately...
[2021-11-02 09:39:20] Done.
Validation 7, 15 remaining
[2021-11-02 09:39:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:20] Number of windows considered: 1...
[2021-11-02 09:39:20] Bias-correcting 1 members separately...
[2021-11-02 09:39:21] Done.
Validation 8, 14 remaining
[2021-11-02 09:39:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:21] Number of windows considered: 1...
[2021-11-02 09:39:21] Bias-correcting 1 members separately...
[2021-11-02 09:39:21] Done.
Validation 9, 13 remaining
[2021-11-02 09:39:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:22] Number of windows considered: 1...
[2021-11-02 09:39:22] Bias-correcting 1 members separately...
[2021-11-02 09:39:22] Done.
Validation 10, 12 remaining
[2021-11-02 09:39:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:23] Number of windows considered: 1...
[2021-11-02 09:39:23] Bias-correcting 1 members separately...
[2021-11-02 09:39:23] Done.
Validation 11, 11 remaining
[2021-11-02 09:39:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:24] Number of windows considered: 1...
[2021-11-02 09:39:24] Bias-correcting 1 members separately...
[2021-11-02 09:39:24] Done.
Validation 12, 10 remaining
[2021-11-02 09:39:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:25] Number of windows considered: 1...
[2021-11-02 09:39:25] Bias-correcting 1 members separately...
[2021-11-02 09:39:25] Done.
Validation 13, 9 remaining
[2021-11-02 09:39:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:25] Number of windows considered: 1...
[2021-11-02 09:39:25] Bias-correcting 1 members separately...
[2021-11-02 09:39:25] Done.
Validation 14, 8 remaining
[2021-11-02 09:39:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:26] Number of windows considered: 1...
[2021-11-02 09:39:26] Bias-correcting 1 members separately...
[2021-11-02 09:39:26] Done.
Validation 15, 7 remaining
[2021-11-02 09:39:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:27] Number of windows considered: 1...
[2021-11-02 09:39:27] Bias-correcting 1 members separately...
[2021-11-02 09:39:27] Done.
Validation 16, 6 remaining
[2021-11-02 09:39:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:28] Number of windows considered: 1...
[2021-11-02 09:39:28] Bias-correcting 1 members separately...
[2021-11-02 09:39:28] Done.
Validation 17, 5 remaining
[2021-11-02 09:39:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:28] Number of windows considered: 1...
[2021-11-02 09:39:28] Bias-correcting 1 members separately...
[2021-11-02 09:39:29] Done.
Validation 18, 4 remaining
[2021-11-02 09:39:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:29] Number of windows considered: 1...
[2021-11-02 09:39:29] Bias-correcting 1 members separately...
[2021-11-02 09:39:29] Done.
Validation 19, 3 remaining
[2021-11-02 09:39:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:30] Number of windows considered: 1...
[2021-11-02 09:39:30] Bias-correcting 1 members separately...
[2021-11-02 09:39:30] Done.
Validation 20, 2 remaining
[2021-11-02 09:39:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:31] Number of windows considered: 1...
[2021-11-02 09:39:31] Bias-correcting 1 members separately...
[2021-11-02 09:39:31] Done.
Validation 21, 1 remaining
[2021-11-02 09:39:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:31] Number of windows considered: 1...
[2021-11-02 09:39:31] Bias-correcting 1 members separately...
[2021-11-02 09:39:31] Done.
Validation 22, 0 remaining
[2021-11-02 09:39:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:32] Number of windows considered: 1...
[2021-11-02 09:39:32] Bias-correcting 1 members separately...
[2021-11-02 09:39:32] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-11-02 09:39:32] Performing annual aggregation...
[2021-11-02 09:39:32] Done.
[2021-11-02 09:39:32] - Computing climatology...
[2021-11-02 09:39:32] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.eqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:39:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:38] Number of windows considered: 1...
[2021-11-02 09:39:38] Bias-correcting 1 members separately...
[2021-11-02 09:39:38] Done.
Validation 2, 20 remaining
[2021-11-02 09:39:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:39] Number of windows considered: 1...
[2021-11-02 09:39:39] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:39:39] Done.
Validation 3, 19 remaining
[2021-11-02 09:39:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:39] Number of windows considered: 1...
[2021-11-02 09:39:39] Bias-correcting 1 members separately...
[2021-11-02 09:39:39] Done.
Validation 4, 18 remaining
[2021-11-02 09:39:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:40] Number of windows considered: 1...
[2021-11-02 09:39:40] Bias-correcting 1 members separately...
[2021-11-02 09:39:40] Done.
Validation 5, 17 remaining
[2021-11-02 09:39:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:41] Number of windows considered: 1...
[2021-11-02 09:39:41] Bias-correcting 1 members separately...
[2021-11-02 09:39:41] Done.
Validation 6, 16 remaining
[2021-11-02 09:39:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:42] Number of windows considered: 1...
[2021-11-02 09:39:42] Bias-correcting 1 members separately...
[2021-11-02 09:39:42] Done.
Validation 7, 15 remaining
[2021-11-02 09:39:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:42] Number of windows considered: 1...
[2021-11-02 09:39:42] Bias-correcting 1 members separately...
[2021-11-02 09:39:42] Done.
Validation 8, 14 remaining
[2021-11-02 09:39:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:43] Number of windows considered: 1...
[2021-11-02 09:39:43] Bias-correcting 1 members separately...
[2021-11-02 09:39:43] Done.
Validation 9, 13 remaining
[2021-11-02 09:39:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:44] Number of windows considered: 1...
[2021-11-02 09:39:44] Bias-correcting 1 members separately...
[2021-11-02 09:39:44] Done.
Validation 10, 12 remaining
[2021-11-02 09:39:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:44] Number of windows considered: 1...
[2021-11-02 09:39:44] Bias-correcting 1 members separately...
[2021-11-02 09:39:44] Done.
Validation 11, 11 remaining
[2021-11-02 09:39:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:45] Number of windows considered: 1...
[2021-11-02 09:39:45] Bias-correcting 1 members separately...
[2021-11-02 09:39:45] Done.
Validation 12, 10 remaining
[2021-11-02 09:39:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:46] Number of windows considered: 1...
[2021-11-02 09:39:46] Bias-correcting 1 members separately...
[2021-11-02 09:39:46] Done.
Validation 13, 9 remaining
[2021-11-02 09:39:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:47] Number of windows considered: 1...
[2021-11-02 09:39:47] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:39:47] Done.
Validation 14, 8 remaining
[2021-11-02 09:39:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:48] Number of windows considered: 1...
[2021-11-02 09:39:48] Bias-correcting 1 members separately...
[2021-11-02 09:39:48] Done.
Validation 15, 7 remaining
[2021-11-02 09:39:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:49] Number of windows considered: 1...
[2021-11-02 09:39:49] Bias-correcting 1 members separately...
[2021-11-02 09:39:49] Done.
Validation 16, 6 remaining
[2021-11-02 09:39:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:49] Number of windows considered: 1...
[2021-11-02 09:39:49] Bias-correcting 1 members separately...
[2021-11-02 09:39:49] Done.
Validation 17, 5 remaining
[2021-11-02 09:39:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:50] Number of windows considered: 1...
[2021-11-02 09:39:50] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:39:50] Done.
Validation 18, 4 remaining
[2021-11-02 09:39:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:51] Number of windows considered: 1...
[2021-11-02 09:39:51] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:39:51] Done.
Validation 19, 3 remaining
[2021-11-02 09:39:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:52] Number of windows considered: 1...
[2021-11-02 09:39:52] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:39:52] Done.
Validation 20, 2 remaining
[2021-11-02 09:39:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:53] Number of windows considered: 1...
[2021-11-02 09:39:53] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:39:53] Done.
Validation 21, 1 remaining
[2021-11-02 09:39:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:53] Number of windows considered: 1...
[2021-11-02 09:39:53] Bias-correcting 1 members separately...
[2021-11-02 09:39:53] Done.
Validation 22, 0 remaining
[2021-11-02 09:39:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:39:54] Number of windows considered: 1...
[2021-11-02 09:39:54] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:39:54] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-11-02 09:39:55] Performing annual aggregation...
[2021-11-02 09:39:55] Done.
[2021-11-02 09:39:55] - Computing climatology...
[2021-11-02 09:39:55] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:40:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:12] Number of windows considered: 1...
[2021-11-02 09:40:12] Bias-correcting 1 members separately...
[2021-11-02 09:40:12] Done.
Validation 2, 20 remaining
[2021-11-02 09:40:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:12] Number of windows considered: 1...
[2021-11-02 09:40:12] Bias-correcting 1 members separately...
[2021-11-02 09:40:12] Done.
Validation 3, 19 remaining
[2021-11-02 09:40:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:13] Number of windows considered: 1...
[2021-11-02 09:40:13] Bias-correcting 1 members separately...
[2021-11-02 09:40:13] Done.
Validation 4, 18 remaining
[2021-11-02 09:40:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:14] Number of windows considered: 1...
[2021-11-02 09:40:14] Bias-correcting 1 members separately...
[2021-11-02 09:40:14] Done.
Validation 5, 17 remaining
[2021-11-02 09:40:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:15] Number of windows considered: 1...
[2021-11-02 09:40:15] Bias-correcting 1 members separately...
[2021-11-02 09:40:15] Done.
Validation 6, 16 remaining
[2021-11-02 09:40:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:16] Number of windows considered: 1...
[2021-11-02 09:40:16] Bias-correcting 1 members separately...
[2021-11-02 09:40:16] Done.
Validation 7, 15 remaining
[2021-11-02 09:40:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:17] Number of windows considered: 1...
[2021-11-02 09:40:17] Bias-correcting 1 members separately...
[2021-11-02 09:40:17] Done.
Validation 8, 14 remaining
[2021-11-02 09:40:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:17] Number of windows considered: 1...
[2021-11-02 09:40:17] Bias-correcting 1 members separately...
[2021-11-02 09:40:17] Done.
Validation 9, 13 remaining
[2021-11-02 09:40:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:18] Number of windows considered: 1...
[2021-11-02 09:40:18] Bias-correcting 1 members separately...
[2021-11-02 09:40:18] Done.
Validation 10, 12 remaining
[2021-11-02 09:40:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:19] Number of windows considered: 1...
[2021-11-02 09:40:19] Bias-correcting 1 members separately...
[2021-11-02 09:40:19] Done.
Validation 11, 11 remaining
[2021-11-02 09:40:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:20] Number of windows considered: 1...
[2021-11-02 09:40:20] Bias-correcting 1 members separately...
[2021-11-02 09:40:20] Done.
Validation 12, 10 remaining
[2021-11-02 09:40:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:21] Number of windows considered: 1...
[2021-11-02 09:40:21] Bias-correcting 1 members separately...
[2021-11-02 09:40:21] Done.
Validation 13, 9 remaining
[2021-11-02 09:40:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:22] Number of windows considered: 1...
[2021-11-02 09:40:22] Bias-correcting 1 members separately...
[2021-11-02 09:40:22] Done.
Validation 14, 8 remaining
[2021-11-02 09:40:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:22] Number of windows considered: 1...
[2021-11-02 09:40:22] Bias-correcting 1 members separately...
[2021-11-02 09:40:22] Done.
Validation 15, 7 remaining
[2021-11-02 09:40:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:23] Number of windows considered: 1...
[2021-11-02 09:40:23] Bias-correcting 1 members separately...
[2021-11-02 09:40:23] Done.
Validation 16, 6 remaining
[2021-11-02 09:40:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:24] Number of windows considered: 1...
[2021-11-02 09:40:24] Bias-correcting 1 members separately...
[2021-11-02 09:40:24] Done.
Validation 17, 5 remaining
[2021-11-02 09:40:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:25] Number of windows considered: 1...
[2021-11-02 09:40:25] Bias-correcting 1 members separately...
[2021-11-02 09:40:25] Done.
Validation 18, 4 remaining
[2021-11-02 09:40:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:26] Number of windows considered: 1...
[2021-11-02 09:40:26] Bias-correcting 1 members separately...
[2021-11-02 09:40:26] Done.
Validation 19, 3 remaining
[2021-11-02 09:40:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:26] Number of windows considered: 1...
[2021-11-02 09:40:26] Bias-correcting 1 members separately...
[2021-11-02 09:40:27] Done.
Validation 20, 2 remaining
[2021-11-02 09:40:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:27] Number of windows considered: 1...
[2021-11-02 09:40:27] Bias-correcting 1 members separately...
[2021-11-02 09:40:27] Done.
Validation 21, 1 remaining
[2021-11-02 09:40:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:28] Number of windows considered: 1...
[2021-11-02 09:40:28] Bias-correcting 1 members separately...
[2021-11-02 09:40:28] Done.
Validation 22, 0 remaining
[2021-11-02 09:40:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:40:29] Number of windows considered: 1...
[2021-11-02 09:40:29] Bias-correcting 1 members separately...
[2021-11-02 09:40:29] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-11-02 09:40:30] Performing annual aggregation...
[2021-11-02 09:40:30] Done.
[2021-11-02 09:40:30] - Computing climatology...
[2021-11-02 09:40:30] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm2.cl2 <- index.cal.station.cl2
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores
GPQM2-WT2 GPQM-WT2 EQM-WT2 PQM-WT2
0.7717906 0.6477915 0.4866396 0.4295075
scores.st3.wt2 <- scores
WT3
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))
station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
[2021-11-02 09:41:00] Performing annual aggregation...
no non-missing arguments to max; returning -Inf[2021-11-02 09:41:00] Done.
[2021-11-02 09:41:00] - Computing climatology...
[2021-11-02 09:41:00] - Done.
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)
index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
[2021-11-02 09:41:00] Performing annual aggregation...
[2021-11-02 09:41:00] Done.
[2021-11-02 09:41:00] - Computing climatology...
[2021-11-02 09:41:00] - Done.
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")
station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:41:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:04] Number of windows considered: 1...
[2021-11-02 09:41:04] Bias-correcting 1 members separately...
[2021-11-02 09:41:04] Done.
Validation 2, 20 remaining
[2021-11-02 09:41:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:05] Number of windows considered: 1...
[2021-11-02 09:41:05] Bias-correcting 1 members separately...
[2021-11-02 09:41:05] Done.
Validation 3, 19 remaining
[2021-11-02 09:41:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:05] Number of windows considered: 1...
[2021-11-02 09:41:05] Bias-correcting 1 members separately...
[2021-11-02 09:41:05] Done.
Validation 4, 18 remaining
[2021-11-02 09:41:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:06] Number of windows considered: 1...
[2021-11-02 09:41:06] Bias-correcting 1 members separately...
[2021-11-02 09:41:06] Done.
Validation 5, 17 remaining
[2021-11-02 09:41:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:07] Number of windows considered: 1...
[2021-11-02 09:41:07] Bias-correcting 1 members separately...
[2021-11-02 09:41:07] Done.
Validation 6, 16 remaining
[2021-11-02 09:41:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:07] Number of windows considered: 1...
[2021-11-02 09:41:07] Bias-correcting 1 members separately...
[2021-11-02 09:41:07] Done.
Validation 7, 15 remaining
[2021-11-02 09:41:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:08] Number of windows considered: 1...
[2021-11-02 09:41:08] Bias-correcting 1 members separately...
[2021-11-02 09:41:08] Done.
Validation 8, 14 remaining
[2021-11-02 09:41:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:09] Number of windows considered: 1...
[2021-11-02 09:41:09] Bias-correcting 1 members separately...
[2021-11-02 09:41:09] Done.
Validation 9, 13 remaining
[2021-11-02 09:41:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:09] Number of windows considered: 1...
[2021-11-02 09:41:10] Bias-correcting 1 members separately...
[2021-11-02 09:41:10] Done.
Validation 10, 12 remaining
[2021-11-02 09:41:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:10] Number of windows considered: 1...
[2021-11-02 09:41:10] Bias-correcting 1 members separately...
[2021-11-02 09:41:10] Done.
Validation 11, 11 remaining
[2021-11-02 09:41:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:11] Number of windows considered: 1...
[2021-11-02 09:41:11] Bias-correcting 1 members separately...
[2021-11-02 09:41:11] Done.
Validation 12, 10 remaining
[2021-11-02 09:41:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:12] Number of windows considered: 1...
[2021-11-02 09:41:12] Bias-correcting 1 members separately...
[2021-11-02 09:41:12] Done.
Validation 13, 9 remaining
[2021-11-02 09:41:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:12] Number of windows considered: 1...
[2021-11-02 09:41:12] Bias-correcting 1 members separately...
[2021-11-02 09:41:13] Done.
Validation 14, 8 remaining
[2021-11-02 09:41:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:13] Number of windows considered: 1...
[2021-11-02 09:41:13] Bias-correcting 1 members separately...
[2021-11-02 09:41:13] Done.
Validation 15, 7 remaining
[2021-11-02 09:41:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:14] Number of windows considered: 1...
[2021-11-02 09:41:14] Bias-correcting 1 members separately...
[2021-11-02 09:41:14] Done.
Validation 16, 6 remaining
[2021-11-02 09:41:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:15] Number of windows considered: 1...
[2021-11-02 09:41:15] Bias-correcting 1 members separately...
[2021-11-02 09:41:15] Done.
Validation 17, 5 remaining
[2021-11-02 09:41:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:15] Number of windows considered: 1...
[2021-11-02 09:41:15] Bias-correcting 1 members separately...
[2021-11-02 09:41:16] Done.
Validation 18, 4 remaining
[2021-11-02 09:41:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:16] Number of windows considered: 1...
[2021-11-02 09:41:16] Bias-correcting 1 members separately...
[2021-11-02 09:41:16] Done.
Validation 19, 3 remaining
[2021-11-02 09:41:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:17] Number of windows considered: 1...
[2021-11-02 09:41:17] Bias-correcting 1 members separately...
[2021-11-02 09:41:17] Done.
Validation 20, 2 remaining
[2021-11-02 09:41:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:18] Number of windows considered: 1...
[2021-11-02 09:41:18] Bias-correcting 1 members separately...
[2021-11-02 09:41:18] Done.
Validation 21, 1 remaining
[2021-11-02 09:41:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:19] Number of windows considered: 1...
[2021-11-02 09:41:19] Bias-correcting 1 members separately...
[2021-11-02 09:41:19] Done.
Validation 22, 0 remaining
[2021-11-02 09:41:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:19] Number of windows considered: 1...
[2021-11-02 09:41:19] Bias-correcting 1 members separately...
[2021-11-02 09:41:19] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-11-02 09:41:20] Performing annual aggregation...
[2021-11-02 09:41:20] Done.
[2021-11-02 09:41:20] - Computing climatology...
[2021-11-02 09:41:20] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.pqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:41:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:28] Number of windows considered: 1...
[2021-11-02 09:41:28] Bias-correcting 1 members separately...
[2021-11-02 09:41:28] Done.
Validation 2, 20 remaining
[2021-11-02 09:41:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:29] Number of windows considered: 1...
[2021-11-02 09:41:29] Bias-correcting 1 members separately...
[2021-11-02 09:41:29] Done.
Validation 3, 19 remaining
[2021-11-02 09:41:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:30] Number of windows considered: 1...
[2021-11-02 09:41:30] Bias-correcting 1 members separately...
[2021-11-02 09:41:30] Done.
Validation 4, 18 remaining
[2021-11-02 09:41:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:30] Number of windows considered: 1...
[2021-11-02 09:41:30] Bias-correcting 1 members separately...
[2021-11-02 09:41:30] Done.
Validation 5, 17 remaining
[2021-11-02 09:41:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:31] Number of windows considered: 1...
[2021-11-02 09:41:31] Bias-correcting 1 members separately...
[2021-11-02 09:41:31] Done.
Validation 6, 16 remaining
[2021-11-02 09:41:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:32] Number of windows considered: 1...
[2021-11-02 09:41:32] Bias-correcting 1 members separately...
[2021-11-02 09:41:32] Done.
Validation 7, 15 remaining
[2021-11-02 09:41:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:33] Number of windows considered: 1...
[2021-11-02 09:41:33] Bias-correcting 1 members separately...
[2021-11-02 09:41:33] Done.
Validation 8, 14 remaining
[2021-11-02 09:41:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:33] Number of windows considered: 1...
[2021-11-02 09:41:33] Bias-correcting 1 members separately...
[2021-11-02 09:41:33] Done.
Validation 9, 13 remaining
[2021-11-02 09:41:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:34] Number of windows considered: 1...
[2021-11-02 09:41:34] Bias-correcting 1 members separately...
[2021-11-02 09:41:34] Done.
Validation 10, 12 remaining
[2021-11-02 09:41:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:35] Number of windows considered: 1...
[2021-11-02 09:41:35] Bias-correcting 1 members separately...
[2021-11-02 09:41:35] Done.
Validation 11, 11 remaining
[2021-11-02 09:41:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:35] Number of windows considered: 1...
[2021-11-02 09:41:35] Bias-correcting 1 members separately...
[2021-11-02 09:41:35] Done.
Validation 12, 10 remaining
[2021-11-02 09:41:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:36] Number of windows considered: 1...
[2021-11-02 09:41:36] Bias-correcting 1 members separately...
[2021-11-02 09:41:36] Done.
Validation 13, 9 remaining
[2021-11-02 09:41:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:37] Number of windows considered: 1...
[2021-11-02 09:41:37] Bias-correcting 1 members separately...
[2021-11-02 09:41:37] Done.
Validation 14, 8 remaining
[2021-11-02 09:41:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:38] Number of windows considered: 1...
[2021-11-02 09:41:38] Bias-correcting 1 members separately...
[2021-11-02 09:41:38] Done.
Validation 15, 7 remaining
[2021-11-02 09:41:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:38] Number of windows considered: 1...
[2021-11-02 09:41:38] Bias-correcting 1 members separately...
[2021-11-02 09:41:38] Done.
Validation 16, 6 remaining
[2021-11-02 09:41:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:39] Number of windows considered: 1...
[2021-11-02 09:41:39] Bias-correcting 1 members separately...
[2021-11-02 09:41:39] Done.
Validation 17, 5 remaining
[2021-11-02 09:41:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:40] Number of windows considered: 1...
[2021-11-02 09:41:40] Bias-correcting 1 members separately...
[2021-11-02 09:41:40] Done.
Validation 18, 4 remaining
[2021-11-02 09:41:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:41] Number of windows considered: 1...
[2021-11-02 09:41:41] Bias-correcting 1 members separately...
[2021-11-02 09:41:41] Done.
Validation 19, 3 remaining
[2021-11-02 09:41:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:41] Number of windows considered: 1...
[2021-11-02 09:41:41] Bias-correcting 1 members separately...
[2021-11-02 09:41:42] Done.
Validation 20, 2 remaining
[2021-11-02 09:41:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:42] Number of windows considered: 1...
[2021-11-02 09:41:42] Bias-correcting 1 members separately...
[2021-11-02 09:41:42] Done.
Validation 21, 1 remaining
[2021-11-02 09:41:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:43] Number of windows considered: 1...
[2021-11-02 09:41:43] Bias-correcting 1 members separately...
[2021-11-02 09:41:43] Done.
Validation 22, 0 remaining
[2021-11-02 09:41:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:44] Number of windows considered: 1...
[2021-11-02 09:41:44] Bias-correcting 1 members separately...
[2021-11-02 09:41:44] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-11-02 09:41:44] Performing annual aggregation...
[2021-11-02 09:41:44] Done.
[2021-11-02 09:41:44] - Computing climatology...
[2021-11-02 09:41:44] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.eqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:41:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:58] Number of windows considered: 1...
[2021-11-02 09:41:58] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:41:58] Done.
Validation 2, 20 remaining
[2021-11-02 09:41:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:59] Number of windows considered: 1...
[2021-11-02 09:41:59] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:41:59] Done.
Validation 3, 19 remaining
[2021-11-02 09:41:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:41:59] Number of windows considered: 1...
[2021-11-02 09:41:59] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:41:59] Done.
Validation 4, 18 remaining
[2021-11-02 09:42:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:00] Number of windows considered: 1...
[2021-11-02 09:42:00] Bias-correcting 1 members separately...
[2021-11-02 09:42:00] Done.
Validation 5, 17 remaining
[2021-11-02 09:42:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:01] Number of windows considered: 1...
[2021-11-02 09:42:01] Bias-correcting 1 members separately...
[2021-11-02 09:42:01] Done.
Validation 6, 16 remaining
[2021-11-02 09:42:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:02] Number of windows considered: 1...
[2021-11-02 09:42:02] Bias-correcting 1 members separately...
[2021-11-02 09:42:02] Done.
Validation 7, 15 remaining
[2021-11-02 09:42:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:02] Number of windows considered: 1...
[2021-11-02 09:42:02] Bias-correcting 1 members separately...
[2021-11-02 09:42:02] Done.
Validation 8, 14 remaining
[2021-11-02 09:42:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:03] Number of windows considered: 1...
[2021-11-02 09:42:03] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:42:03] Done.
Validation 9, 13 remaining
[2021-11-02 09:42:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:04] Number of windows considered: 1...
[2021-11-02 09:42:04] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:42:04] Done.
Validation 10, 12 remaining
[2021-11-02 09:42:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:05] Number of windows considered: 1...
[2021-11-02 09:42:05] Bias-correcting 1 members separately...
[2021-11-02 09:42:05] Done.
Validation 11, 11 remaining
[2021-11-02 09:42:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:06] Number of windows considered: 1...
[2021-11-02 09:42:06] Bias-correcting 1 members separately...
[2021-11-02 09:42:06] Done.
Validation 12, 10 remaining
[2021-11-02 09:42:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:06] Number of windows considered: 1...
[2021-11-02 09:42:06] Bias-correcting 1 members separately...
[2021-11-02 09:42:06] Done.
Validation 13, 9 remaining
[2021-11-02 09:42:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:07] Number of windows considered: 1...
[2021-11-02 09:42:07] Bias-correcting 1 members separately...
[2021-11-02 09:42:07] Done.
Validation 14, 8 remaining
[2021-11-02 09:42:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:08] Number of windows considered: 1...
[2021-11-02 09:42:08] Bias-correcting 1 members separately...
[2021-11-02 09:42:08] Done.
Validation 15, 7 remaining
[2021-11-02 09:42:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:09] Number of windows considered: 1...
[2021-11-02 09:42:09] Bias-correcting 1 members separately...
[2021-11-02 09:42:09] Done.
Validation 16, 6 remaining
[2021-11-02 09:42:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:10] Number of windows considered: 1...
[2021-11-02 09:42:10] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:42:10] Done.
Validation 17, 5 remaining
[2021-11-02 09:42:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:10] Number of windows considered: 1...
[2021-11-02 09:42:10] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:42:10] Done.
Validation 18, 4 remaining
[2021-11-02 09:42:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:11] Number of windows considered: 1...
[2021-11-02 09:42:11] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:42:11] Done.
Validation 19, 3 remaining
[2021-11-02 09:42:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:12] Number of windows considered: 1...
[2021-11-02 09:42:12] Bias-correcting 1 members separately...
[2021-11-02 09:42:12] Done.
Validation 20, 2 remaining
[2021-11-02 09:42:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:13] Number of windows considered: 1...
[2021-11-02 09:42:13] Bias-correcting 1 members separately...
[2021-11-02 09:42:13] Done.
Validation 21, 1 remaining
[2021-11-02 09:42:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:14] Number of windows considered: 1...
[2021-11-02 09:42:14] Bias-correcting 1 members separately...
[2021-11-02 09:42:14] Done.
Validation 22, 0 remaining
[2021-11-02 09:42:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:14] Number of windows considered: 1...
[2021-11-02 09:42:14] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:42:14] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-11-02 09:42:15] Performing annual aggregation...
[2021-11-02 09:42:15] Done.
[2021-11-02 09:42:15] - Computing climatology...
[2021-11-02 09:42:15] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:42:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:24] Number of windows considered: 1...
[2021-11-02 09:42:24] Bias-correcting 1 members separately...
[2021-11-02 09:42:24] Done.
Validation 2, 20 remaining
[2021-11-02 09:42:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:25] Number of windows considered: 1...
[2021-11-02 09:42:25] Bias-correcting 1 members separately...
[2021-11-02 09:42:25] Done.
Validation 3, 19 remaining
[2021-11-02 09:42:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:26] Number of windows considered: 1...
[2021-11-02 09:42:26] Bias-correcting 1 members separately...
[2021-11-02 09:42:26] Done.
Validation 4, 18 remaining
[2021-11-02 09:42:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:26] Number of windows considered: 1...
[2021-11-02 09:42:26] Bias-correcting 1 members separately...
[2021-11-02 09:42:26] Done.
Validation 5, 17 remaining
[2021-11-02 09:42:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:27] Number of windows considered: 1...
[2021-11-02 09:42:27] Bias-correcting 1 members separately...
[2021-11-02 09:42:27] Done.
Validation 6, 16 remaining
[2021-11-02 09:42:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:27] Number of windows considered: 1...
[2021-11-02 09:42:27] Bias-correcting 1 members separately...
[2021-11-02 09:42:27] Done.
Validation 7, 15 remaining
[2021-11-02 09:42:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:28] Number of windows considered: 1...
[2021-11-02 09:42:28] Bias-correcting 1 members separately...
[2021-11-02 09:42:28] Done.
Validation 8, 14 remaining
[2021-11-02 09:42:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:29] Number of windows considered: 1...
[2021-11-02 09:42:29] Bias-correcting 1 members separately...
[2021-11-02 09:42:29] Done.
Validation 9, 13 remaining
[2021-11-02 09:42:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:29] Number of windows considered: 1...
[2021-11-02 09:42:29] Bias-correcting 1 members separately...
[2021-11-02 09:42:29] Done.
Validation 10, 12 remaining
[2021-11-02 09:42:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:30] Number of windows considered: 1...
[2021-11-02 09:42:30] Bias-correcting 1 members separately...
[2021-11-02 09:42:30] Done.
Validation 11, 11 remaining
[2021-11-02 09:42:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:31] Number of windows considered: 1...
[2021-11-02 09:42:31] Bias-correcting 1 members separately...
[2021-11-02 09:42:31] Done.
Validation 12, 10 remaining
[2021-11-02 09:42:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:32] Number of windows considered: 1...
[2021-11-02 09:42:32] Bias-correcting 1 members separately...
[2021-11-02 09:42:32] Done.
Validation 13, 9 remaining
[2021-11-02 09:42:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:32] Number of windows considered: 1...
[2021-11-02 09:42:32] Bias-correcting 1 members separately...
[2021-11-02 09:42:32] Done.
Validation 14, 8 remaining
[2021-11-02 09:42:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:33] Number of windows considered: 1...
[2021-11-02 09:42:33] Bias-correcting 1 members separately...
[2021-11-02 09:42:33] Done.
Validation 15, 7 remaining
[2021-11-02 09:42:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:34] Number of windows considered: 1...
[2021-11-02 09:42:34] Bias-correcting 1 members separately...
[2021-11-02 09:42:34] Done.
Validation 16, 6 remaining
[2021-11-02 09:42:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:34] Number of windows considered: 1...
[2021-11-02 09:42:34] Bias-correcting 1 members separately...
[2021-11-02 09:42:34] Done.
Validation 17, 5 remaining
[2021-11-02 09:42:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:35] Number of windows considered: 1...
[2021-11-02 09:42:35] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:42:35] Done.
Validation 18, 4 remaining
[2021-11-02 09:42:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:36] Number of windows considered: 1...
[2021-11-02 09:42:36] Bias-correcting 1 members separately...
[2021-11-02 09:42:36] Done.
Validation 19, 3 remaining
[2021-11-02 09:42:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:37] Number of windows considered: 1...
[2021-11-02 09:42:37] Bias-correcting 1 members separately...
[2021-11-02 09:42:37] Done.
Validation 20, 2 remaining
[2021-11-02 09:42:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:37] Number of windows considered: 1...
[2021-11-02 09:42:37] Bias-correcting 1 members separately...
[2021-11-02 09:42:37] Done.
Validation 21, 1 remaining
[2021-11-02 09:42:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:38] Number of windows considered: 1...
[2021-11-02 09:42:38] Bias-correcting 1 members separately...
[2021-11-02 09:42:38] Done.
Validation 22, 0 remaining
[2021-11-02 09:42:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:42:39] Number of windows considered: 1...
[2021-11-02 09:42:39] Bias-correcting 1 members separately...
[2021-11-02 09:42:39] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-11-02 09:42:39] Performing annual aggregation...
[2021-11-02 09:42:39] Done.
[2021-11-02 09:42:39] - Computing climatology...
[2021-11-02 09:42:39] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm2.cl3 <- index.cal.station.cl3
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
GPQM2-WT3 GPQM-WT3 EQM-WT3 PQM-WT3
0.5083505 0.4184974 0.3933047 0.3912786
scores.st3.wt3 <- scores
WT4
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))
station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
[2021-11-02 09:43:08] Performing annual aggregation...
no non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Inf[2021-11-02 09:43:08] Done.
[2021-11-02 09:43:08] - Computing climatology...
[2021-11-02 09:43:08] - Done.
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)
index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
[2021-11-02 09:43:08] Performing annual aggregation...
[2021-11-02 09:43:08] Done.
[2021-11-02 09:43:08] - Computing climatology...
[2021-11-02 09:43:08] - Done.
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")
station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:43:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:11] Number of windows considered: 1...
[2021-11-02 09:43:11] Bias-correcting 1 members separately...
[2021-11-02 09:43:11] Done.
Validation 2, 20 remaining
[2021-11-02 09:43:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:12] Number of windows considered: 1...
[2021-11-02 09:43:12] Bias-correcting 1 members separately...
[2021-11-02 09:43:12] Done.
Validation 3, 19 remaining
[2021-11-02 09:43:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:13] Number of windows considered: 1...
[2021-11-02 09:43:13] Bias-correcting 1 members separately...
[2021-11-02 09:43:13] Done.
Validation 4, 18 remaining
[2021-11-02 09:43:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:14] Number of windows considered: 1...
[2021-11-02 09:43:14] Bias-correcting 1 members separately...
[2021-11-02 09:43:14] Done.
Validation 5, 17 remaining
[2021-11-02 09:43:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:14] Number of windows considered: 1...
[2021-11-02 09:43:14] Bias-correcting 1 members separately...
[2021-11-02 09:43:14] Done.
Validation 6, 16 remaining
[2021-11-02 09:43:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:15] Number of windows considered: 1...
[2021-11-02 09:43:15] Bias-correcting 1 members separately...
[2021-11-02 09:43:15] Done.
Validation 7, 15 remaining
[2021-11-02 09:43:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:16] Number of windows considered: 1...
[2021-11-02 09:43:16] Bias-correcting 1 members separately...
[2021-11-02 09:43:16] Done.
Validation 8, 14 remaining
[2021-11-02 09:43:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:17] Number of windows considered: 1...
[2021-11-02 09:43:17] Bias-correcting 1 members separately...
[2021-11-02 09:43:17] Done.
Validation 9, 13 remaining
[2021-11-02 09:43:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:17] Number of windows considered: 1...
[2021-11-02 09:43:17] Bias-correcting 1 members separately...
[2021-11-02 09:43:17] Done.
Validation 10, 12 remaining
[2021-11-02 09:43:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:18] Number of windows considered: 1...
[2021-11-02 09:43:18] Bias-correcting 1 members separately...
[2021-11-02 09:43:18] Done.
Validation 11, 11 remaining
[2021-11-02 09:43:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:19] Number of windows considered: 1...
[2021-11-02 09:43:19] Bias-correcting 1 members separately...
[2021-11-02 09:43:19] Done.
Validation 12, 10 remaining
[2021-11-02 09:43:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:20] Number of windows considered: 1...
[2021-11-02 09:43:20] Bias-correcting 1 members separately...
[2021-11-02 09:43:20] Done.
Validation 13, 9 remaining
[2021-11-02 09:43:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:20] Number of windows considered: 1...
[2021-11-02 09:43:20] Bias-correcting 1 members separately...
[2021-11-02 09:43:20] Done.
Validation 14, 8 remaining
[2021-11-02 09:43:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:21] Number of windows considered: 1...
[2021-11-02 09:43:21] Bias-correcting 1 members separately...
[2021-11-02 09:43:21] Done.
Validation 15, 7 remaining
[2021-11-02 09:43:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:22] Number of windows considered: 1...
[2021-11-02 09:43:22] Bias-correcting 1 members separately...
[2021-11-02 09:43:22] Done.
Validation 16, 6 remaining
[2021-11-02 09:43:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:22] Number of windows considered: 1...
[2021-11-02 09:43:22] Bias-correcting 1 members separately...
[2021-11-02 09:43:22] Done.
Validation 17, 5 remaining
[2021-11-02 09:43:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:23] Number of windows considered: 1...
[2021-11-02 09:43:23] Bias-correcting 1 members separately...
[2021-11-02 09:43:23] Done.
Validation 18, 4 remaining
[2021-11-02 09:43:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:23] Number of windows considered: 1...
[2021-11-02 09:43:23] Bias-correcting 1 members separately...
[2021-11-02 09:43:23] Done.
Validation 19, 3 remaining
[2021-11-02 09:43:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:24] Number of windows considered: 1...
[2021-11-02 09:43:24] Bias-correcting 1 members separately...
[2021-11-02 09:43:24] Done.
Validation 20, 2 remaining
[2021-11-02 09:43:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:25] Number of windows considered: 1...
[2021-11-02 09:43:25] Bias-correcting 1 members separately...
[2021-11-02 09:43:25] Done.
Validation 21, 1 remaining
[2021-11-02 09:43:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:25] Number of windows considered: 1...
[2021-11-02 09:43:25] Bias-correcting 1 members separately...
[2021-11-02 09:43:25] Done.
Validation 22, 0 remaining
[2021-11-02 09:43:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:43:26] Number of windows considered: 1...
[2021-11-02 09:43:26] Bias-correcting 1 members separately...
[2021-11-02 09:43:26] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-11-02 09:43:27] Performing annual aggregation...
[2021-11-02 09:43:27] Done.
[2021-11-02 09:43:27] - Computing climatology...
[2021-11-02 09:43:27] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.pqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:44:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:44] Number of windows considered: 1...
[2021-11-02 09:44:44] Bias-correcting 1 members separately...
[2021-11-02 09:44:44] Done.
Validation 2, 20 remaining
[2021-11-02 09:44:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:45] Number of windows considered: 1...
[2021-11-02 09:44:45] Bias-correcting 1 members separately...
[2021-11-02 09:44:45] Done.
Validation 3, 19 remaining
[2021-11-02 09:44:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:46] Number of windows considered: 1...
[2021-11-02 09:44:46] Bias-correcting 1 members separately...
[2021-11-02 09:44:46] Done.
Validation 4, 18 remaining
[2021-11-02 09:44:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:47] Number of windows considered: 1...
[2021-11-02 09:44:47] Bias-correcting 1 members separately...
[2021-11-02 09:44:47] Done.
Validation 5, 17 remaining
[2021-11-02 09:44:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:47] Number of windows considered: 1...
[2021-11-02 09:44:47] Bias-correcting 1 members separately...
[2021-11-02 09:44:47] Done.
Validation 6, 16 remaining
[2021-11-02 09:44:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:48] Number of windows considered: 1...
[2021-11-02 09:44:48] Bias-correcting 1 members separately...
[2021-11-02 09:44:48] Done.
Validation 7, 15 remaining
[2021-11-02 09:44:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:49] Number of windows considered: 1...
[2021-11-02 09:44:49] Bias-correcting 1 members separately...
[2021-11-02 09:44:49] Done.
Validation 8, 14 remaining
[2021-11-02 09:44:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:50] Number of windows considered: 1...
[2021-11-02 09:44:50] Bias-correcting 1 members separately...
[2021-11-02 09:44:50] Done.
Validation 9, 13 remaining
[2021-11-02 09:44:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:50] Number of windows considered: 1...
[2021-11-02 09:44:50] Bias-correcting 1 members separately...
[2021-11-02 09:44:50] Done.
Validation 10, 12 remaining
[2021-11-02 09:44:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:51] Number of windows considered: 1...
[2021-11-02 09:44:51] Bias-correcting 1 members separately...
[2021-11-02 09:44:51] Done.
Validation 11, 11 remaining
[2021-11-02 09:44:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:52] Number of windows considered: 1...
[2021-11-02 09:44:52] Bias-correcting 1 members separately...
[2021-11-02 09:44:52] Done.
Validation 12, 10 remaining
[2021-11-02 09:44:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:53] Number of windows considered: 1...
[2021-11-02 09:44:53] Bias-correcting 1 members separately...
[2021-11-02 09:44:53] Done.
Validation 13, 9 remaining
[2021-11-02 09:44:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:53] Number of windows considered: 1...
[2021-11-02 09:44:53] Bias-correcting 1 members separately...
[2021-11-02 09:44:54] Done.
Validation 14, 8 remaining
[2021-11-02 09:44:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:54] Number of windows considered: 1...
[2021-11-02 09:44:54] Bias-correcting 1 members separately...
[2021-11-02 09:44:54] Done.
Validation 15, 7 remaining
[2021-11-02 09:44:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:55] Number of windows considered: 1...
[2021-11-02 09:44:55] Bias-correcting 1 members separately...
[2021-11-02 09:44:55] Done.
Validation 16, 6 remaining
[2021-11-02 09:44:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:56] Number of windows considered: 1...
[2021-11-02 09:44:56] Bias-correcting 1 members separately...
[2021-11-02 09:44:56] Done.
Validation 17, 5 remaining
[2021-11-02 09:44:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:56] Number of windows considered: 1...
[2021-11-02 09:44:56] Bias-correcting 1 members separately...
[2021-11-02 09:44:57] Done.
Validation 18, 4 remaining
[2021-11-02 09:44:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:57] Number of windows considered: 1...
[2021-11-02 09:44:57] Bias-correcting 1 members separately...
[2021-11-02 09:44:57] Done.
Validation 19, 3 remaining
[2021-11-02 09:44:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:58] Number of windows considered: 1...
[2021-11-02 09:44:58] Bias-correcting 1 members separately...
[2021-11-02 09:44:58] Done.
Validation 20, 2 remaining
[2021-11-02 09:44:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:59] Number of windows considered: 1...
[2021-11-02 09:44:59] Bias-correcting 1 members separately...
[2021-11-02 09:44:59] Done.
Validation 21, 1 remaining
[2021-11-02 09:44:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:44:59] Number of windows considered: 1...
[2021-11-02 09:44:59] Bias-correcting 1 members separately...
[2021-11-02 09:44:59] Done.
Validation 22, 0 remaining
[2021-11-02 09:45:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:00] Number of windows considered: 1...
[2021-11-02 09:45:00] Bias-correcting 1 members separately...
[2021-11-02 09:45:00] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-11-02 09:45:01] Performing annual aggregation...
[2021-11-02 09:45:01] Done.
[2021-11-02 09:45:01] - Computing climatology...
[2021-11-02 09:45:01] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.eqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:45:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:17] Number of windows considered: 1...
[2021-11-02 09:45:17] Bias-correcting 1 members separately...
[2021-11-02 09:45:17] Done.
Validation 2, 20 remaining
[2021-11-02 09:45:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:17] Number of windows considered: 1...
[2021-11-02 09:45:17] Bias-correcting 1 members separately...
[2021-11-02 09:45:17] Done.
Validation 3, 19 remaining
[2021-11-02 09:45:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:18] Number of windows considered: 1...
[2021-11-02 09:45:18] Bias-correcting 1 members separately...
[2021-11-02 09:45:18] Done.
Validation 4, 18 remaining
[2021-11-02 09:45:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:19] Number of windows considered: 1...
[2021-11-02 09:45:19] Bias-correcting 1 members separately...
[2021-11-02 09:45:19] Done.
Validation 5, 17 remaining
[2021-11-02 09:45:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:20] Number of windows considered: 1...
[2021-11-02 09:45:20] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:45:20] Done.
Validation 6, 16 remaining
[2021-11-02 09:45:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:20] Number of windows considered: 1...
[2021-11-02 09:45:20] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:45:20] Done.
Validation 7, 15 remaining
[2021-11-02 09:45:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:21] Number of windows considered: 1...
[2021-11-02 09:45:21] Bias-correcting 1 members separately...
optimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:45:21] Done.
Validation 8, 14 remaining
[2021-11-02 09:45:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:22] Number of windows considered: 1...
[2021-11-02 09:45:22] Bias-correcting 1 members separately...
[2021-11-02 09:45:22] Done.
Validation 9, 13 remaining
[2021-11-02 09:45:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:23] Number of windows considered: 1...
[2021-11-02 09:45:23] Bias-correcting 1 members separately...
optimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:45:23] Done.
Validation 10, 12 remaining
[2021-11-02 09:45:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:23] Number of windows considered: 1...
[2021-11-02 09:45:23] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:45:23] Done.
Validation 11, 11 remaining
[2021-11-02 09:45:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:24] Number of windows considered: 1...
[2021-11-02 09:45:24] Bias-correcting 1 members separately...
[2021-11-02 09:45:24] Done.
Validation 12, 10 remaining
[2021-11-02 09:45:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:25] Number of windows considered: 1...
[2021-11-02 09:45:25] Bias-correcting 1 members separately...
[2021-11-02 09:45:25] Done.
Validation 13, 9 remaining
[2021-11-02 09:45:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:26] Number of windows considered: 1...
[2021-11-02 09:45:26] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:45:26] Done.
Validation 14, 8 remaining
[2021-11-02 09:45:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:26] Number of windows considered: 1...
[2021-11-02 09:45:26] Bias-correcting 1 members separately...
[2021-11-02 09:45:26] Done.
Validation 15, 7 remaining
[2021-11-02 09:45:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:27] Number of windows considered: 1...
[2021-11-02 09:45:27] Bias-correcting 1 members separately...
[2021-11-02 09:45:27] Done.
Validation 16, 6 remaining
[2021-11-02 09:45:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:28] Number of windows considered: 1...
[2021-11-02 09:45:28] Bias-correcting 1 members separately...
optimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:45:28] Done.
Validation 17, 5 remaining
[2021-11-02 09:45:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:29] Number of windows considered: 1...
[2021-11-02 09:45:29] Bias-correcting 1 members separately...
[2021-11-02 09:45:29] Done.
Validation 18, 4 remaining
[2021-11-02 09:45:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:29] Number of windows considered: 1...
[2021-11-02 09:45:29] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:45:29] Done.
Validation 19, 3 remaining
[2021-11-02 09:45:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:30] Number of windows considered: 1...
[2021-11-02 09:45:30] Bias-correcting 1 members separately...
[2021-11-02 09:45:30] Done.
Validation 20, 2 remaining
[2021-11-02 09:45:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:31] Number of windows considered: 1...
[2021-11-02 09:45:31] Bias-correcting 1 members separately...
[2021-11-02 09:45:31] Done.
Validation 21, 1 remaining
[2021-11-02 09:45:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:32] Number of windows considered: 1...
[2021-11-02 09:45:32] Bias-correcting 1 members separately...
[2021-11-02 09:45:32] Done.
Validation 22, 0 remaining
[2021-11-02 09:45:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:32] Number of windows considered: 1...
[2021-11-02 09:45:32] Bias-correcting 1 members separately...
optimization may not have succeeded[2021-11-02 09:45:32] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-11-02 09:45:33] Performing annual aggregation...
[2021-11-02 09:45:33] Done.
[2021-11-02 09:45:33] - Computing climatology...
[2021-11-02 09:45:33] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:45:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:52] Number of windows considered: 1...
[2021-11-02 09:45:52] Bias-correcting 1 members separately...
[2021-11-02 09:45:52] Done.
Validation 2, 20 remaining
[2021-11-02 09:45:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:52] Number of windows considered: 1...
[2021-11-02 09:45:52] Bias-correcting 1 members separately...
[2021-11-02 09:45:52] Done.
Validation 3, 19 remaining
[2021-11-02 09:45:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:53] Number of windows considered: 1...
[2021-11-02 09:45:53] Bias-correcting 1 members separately...
[2021-11-02 09:45:53] Done.
Validation 4, 18 remaining
[2021-11-02 09:45:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:54] Number of windows considered: 1...
[2021-11-02 09:45:54] Bias-correcting 1 members separately...
[2021-11-02 09:45:54] Done.
Validation 5, 17 remaining
[2021-11-02 09:45:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:54] Number of windows considered: 1...
[2021-11-02 09:45:54] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:45:54] Done.
Validation 6, 16 remaining
[2021-11-02 09:45:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:55] Number of windows considered: 1...
[2021-11-02 09:45:55] Bias-correcting 1 members separately...
[2021-11-02 09:45:55] Done.
Validation 7, 15 remaining
[2021-11-02 09:45:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:56] Number of windows considered: 1...
[2021-11-02 09:45:56] Bias-correcting 1 members separately...
[2021-11-02 09:45:56] Done.
Validation 8, 14 remaining
[2021-11-02 09:45:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:56] Number of windows considered: 1...
[2021-11-02 09:45:56] Bias-correcting 1 members separately...
[2021-11-02 09:45:57] Done.
Validation 9, 13 remaining
[2021-11-02 09:45:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:57] Number of windows considered: 1...
[2021-11-02 09:45:57] Bias-correcting 1 members separately...
[2021-11-02 09:45:57] Done.
Validation 10, 12 remaining
[2021-11-02 09:45:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:58] Number of windows considered: 1...
[2021-11-02 09:45:58] Bias-correcting 1 members separately...
[2021-11-02 09:45:58] Done.
Validation 11, 11 remaining
[2021-11-02 09:45:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:59] Number of windows considered: 1...
[2021-11-02 09:45:59] Bias-correcting 1 members separately...
[2021-11-02 09:45:59] Done.
Validation 12, 10 remaining
[2021-11-02 09:45:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:45:59] Number of windows considered: 1...
[2021-11-02 09:45:59] Bias-correcting 1 members separately...
[2021-11-02 09:45:59] Done.
Validation 13, 9 remaining
[2021-11-02 09:46:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:00] Number of windows considered: 1...
[2021-11-02 09:46:00] Bias-correcting 1 members separately...
[2021-11-02 09:46:00] Done.
Validation 14, 8 remaining
[2021-11-02 09:46:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:01] Number of windows considered: 1...
[2021-11-02 09:46:01] Bias-correcting 1 members separately...
[2021-11-02 09:46:01] Done.
Validation 15, 7 remaining
[2021-11-02 09:46:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:01] Number of windows considered: 1...
[2021-11-02 09:46:01] Bias-correcting 1 members separately...
[2021-11-02 09:46:01] Done.
Validation 16, 6 remaining
[2021-11-02 09:46:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:02] Number of windows considered: 1...
[2021-11-02 09:46:02] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:46:02] Done.
Validation 17, 5 remaining
[2021-11-02 09:46:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:03] Number of windows considered: 1...
[2021-11-02 09:46:03] Bias-correcting 1 members separately...
[2021-11-02 09:46:03] Done.
Validation 18, 4 remaining
[2021-11-02 09:46:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:04] Number of windows considered: 1...
[2021-11-02 09:46:04] Bias-correcting 1 members separately...
[2021-11-02 09:46:04] Done.
Validation 19, 3 remaining
[2021-11-02 09:46:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:04] Number of windows considered: 1...
[2021-11-02 09:46:04] Bias-correcting 1 members separately...
[2021-11-02 09:46:04] Done.
Validation 20, 2 remaining
[2021-11-02 09:46:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:05] Number of windows considered: 1...
[2021-11-02 09:46:05] Bias-correcting 1 members separately...
[2021-11-02 09:46:05] Done.
Validation 21, 1 remaining
[2021-11-02 09:46:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:06] Number of windows considered: 1...
[2021-11-02 09:46:06] Bias-correcting 1 members separately...
[2021-11-02 09:46:06] Done.
Validation 22, 0 remaining
[2021-11-02 09:46:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:06] Number of windows considered: 1...
[2021-11-02 09:46:06] Bias-correcting 1 members separately...
[2021-11-02 09:46:06] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-11-02 09:46:07] Performing annual aggregation...
[2021-11-02 09:46:07] Done.
[2021-11-02 09:46:07] - Computing climatology...
[2021-11-02 09:46:07] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm2.cl4 <- index.cal.station.cl4
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)
scores
GPQM-WT4 GPQM2-WT4 EQM-WT4 PQM-WT4
0.6636515 0.5710907 0.5251858 0.2953432
scores.st3.wt4 <- scores
WT5
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))
station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
[2021-11-02 09:46:39] Performing annual aggregation...
no non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Inf[2021-11-02 09:46:39] Done.
[2021-11-02 09:46:39] - Computing climatology...
[2021-11-02 09:46:39] - Done.
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)
index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
[2021-11-02 09:46:39] Performing annual aggregation...
[2021-11-02 09:46:39] Done.
[2021-11-02 09:46:39] - Computing climatology...
[2021-11-02 09:46:39] - Done.
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")
station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:46:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:43] Number of windows considered: 1...
[2021-11-02 09:46:43] Bias-correcting 1 members separately...
[2021-11-02 09:46:43] Done.
Validation 2, 20 remaining
[2021-11-02 09:46:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:44] Number of windows considered: 1...
[2021-11-02 09:46:44] Bias-correcting 1 members separately...
[2021-11-02 09:46:44] Done.
Validation 3, 19 remaining
[2021-11-02 09:46:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:45] Number of windows considered: 1...
[2021-11-02 09:46:45] Bias-correcting 1 members separately...
[2021-11-02 09:46:45] Done.
Validation 4, 18 remaining
[2021-11-02 09:46:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:45] Number of windows considered: 1...
[2021-11-02 09:46:45] Bias-correcting 1 members separately...
[2021-11-02 09:46:46] Done.
Validation 5, 17 remaining
[2021-11-02 09:46:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:46] Number of windows considered: 1...
[2021-11-02 09:46:46] Bias-correcting 1 members separately...
[2021-11-02 09:46:46] Done.
Validation 6, 16 remaining
[2021-11-02 09:46:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:47] Number of windows considered: 1...
[2021-11-02 09:46:47] Bias-correcting 1 members separately...
[2021-11-02 09:46:47] Done.
Validation 7, 15 remaining
[2021-11-02 09:46:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:48] Number of windows considered: 1...
[2021-11-02 09:46:48] Bias-correcting 1 members separately...
[2021-11-02 09:46:48] Done.
Validation 8, 14 remaining
[2021-11-02 09:46:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:48] Number of windows considered: 1...
[2021-11-02 09:46:48] Bias-correcting 1 members separately...
[2021-11-02 09:46:48] Done.
Validation 9, 13 remaining
[2021-11-02 09:46:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:49] Number of windows considered: 1...
[2021-11-02 09:46:49] Bias-correcting 1 members separately...
[2021-11-02 09:46:49] Done.
Validation 10, 12 remaining
[2021-11-02 09:46:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:50] Number of windows considered: 1...
[2021-11-02 09:46:50] Bias-correcting 1 members separately...
[2021-11-02 09:46:50] Done.
Validation 11, 11 remaining
[2021-11-02 09:46:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:51] Number of windows considered: 1...
[2021-11-02 09:46:51] Bias-correcting 1 members separately...
[2021-11-02 09:46:51] Done.
Validation 12, 10 remaining
[2021-11-02 09:46:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:51] Number of windows considered: 1...
[2021-11-02 09:46:51] Bias-correcting 1 members separately...
[2021-11-02 09:46:52] Done.
Validation 13, 9 remaining
[2021-11-02 09:46:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:52] Number of windows considered: 1...
[2021-11-02 09:46:52] Bias-correcting 1 members separately...
[2021-11-02 09:46:53] Done.
Validation 14, 8 remaining
[2021-11-02 09:46:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:53] Number of windows considered: 1...
[2021-11-02 09:46:53] Bias-correcting 1 members separately...
[2021-11-02 09:46:53] Done.
Validation 15, 7 remaining
[2021-11-02 09:46:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:54] Number of windows considered: 1...
[2021-11-02 09:46:54] Bias-correcting 1 members separately...
[2021-11-02 09:46:54] Done.
Validation 16, 6 remaining
[2021-11-02 09:46:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:54] Number of windows considered: 1...
[2021-11-02 09:46:54] Bias-correcting 1 members separately...
[2021-11-02 09:46:54] Done.
Validation 17, 5 remaining
[2021-11-02 09:46:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:55] Number of windows considered: 1...
[2021-11-02 09:46:55] Bias-correcting 1 members separately...
[2021-11-02 09:46:55] Done.
Validation 18, 4 remaining
[2021-11-02 09:46:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:56] Number of windows considered: 1...
[2021-11-02 09:46:56] Bias-correcting 1 members separately...
[2021-11-02 09:46:56] Done.
Validation 19, 3 remaining
[2021-11-02 09:46:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:57] Number of windows considered: 1...
[2021-11-02 09:46:57] Bias-correcting 1 members separately...
[2021-11-02 09:46:57] Done.
Validation 20, 2 remaining
[2021-11-02 09:46:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:57] Number of windows considered: 1...
[2021-11-02 09:46:57] Bias-correcting 1 members separately...
[2021-11-02 09:46:57] Done.
Validation 21, 1 remaining
[2021-11-02 09:46:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:58] Number of windows considered: 1...
[2021-11-02 09:46:58] Bias-correcting 1 members separately...
[2021-11-02 09:46:58] Done.
Validation 22, 0 remaining
[2021-11-02 09:46:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:46:59] Number of windows considered: 1...
[2021-11-02 09:46:59] Bias-correcting 1 members separately...
[2021-11-02 09:46:59] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-11-02 09:46:59] Performing annual aggregation...
[2021-11-02 09:46:59] Done.
[2021-11-02 09:46:59] - Computing climatology...
[2021-11-02 09:46:59] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.pqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:47:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:23] Number of windows considered: 1...
[2021-11-02 09:47:23] Bias-correcting 1 members separately...
[2021-11-02 09:47:23] Done.
Validation 2, 20 remaining
[2021-11-02 09:47:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:24] Number of windows considered: 1...
[2021-11-02 09:47:24] Bias-correcting 1 members separately...
[2021-11-02 09:47:24] Done.
Validation 3, 19 remaining
[2021-11-02 09:47:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:24] Number of windows considered: 1...
[2021-11-02 09:47:24] Bias-correcting 1 members separately...
[2021-11-02 09:47:25] Done.
Validation 4, 18 remaining
[2021-11-02 09:47:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:25] Number of windows considered: 1...
[2021-11-02 09:47:25] Bias-correcting 1 members separately...
[2021-11-02 09:47:25] Done.
Validation 5, 17 remaining
[2021-11-02 09:47:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:26] Number of windows considered: 1...
[2021-11-02 09:47:26] Bias-correcting 1 members separately...
[2021-11-02 09:47:26] Done.
Validation 6, 16 remaining
[2021-11-02 09:47:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:27] Number of windows considered: 1...
[2021-11-02 09:47:27] Bias-correcting 1 members separately...
[2021-11-02 09:47:27] Done.
Validation 7, 15 remaining
[2021-11-02 09:47:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:28] Number of windows considered: 1...
[2021-11-02 09:47:28] Bias-correcting 1 members separately...
[2021-11-02 09:47:28] Done.
Validation 8, 14 remaining
[2021-11-02 09:47:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:29] Number of windows considered: 1...
[2021-11-02 09:47:29] Bias-correcting 1 members separately...
[2021-11-02 09:47:29] Done.
Validation 9, 13 remaining
[2021-11-02 09:47:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:29] Number of windows considered: 1...
[2021-11-02 09:47:29] Bias-correcting 1 members separately...
[2021-11-02 09:47:29] Done.
Validation 10, 12 remaining
[2021-11-02 09:47:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:30] Number of windows considered: 1...
[2021-11-02 09:47:30] Bias-correcting 1 members separately...
[2021-11-02 09:47:30] Done.
Validation 11, 11 remaining
[2021-11-02 09:47:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:31] Number of windows considered: 1...
[2021-11-02 09:47:31] Bias-correcting 1 members separately...
[2021-11-02 09:47:31] Done.
Validation 12, 10 remaining
[2021-11-02 09:47:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:32] Number of windows considered: 1...
[2021-11-02 09:47:32] Bias-correcting 1 members separately...
[2021-11-02 09:47:32] Done.
Validation 13, 9 remaining
[2021-11-02 09:47:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:32] Number of windows considered: 1...
[2021-11-02 09:47:32] Bias-correcting 1 members separately...
[2021-11-02 09:47:33] Done.
Validation 14, 8 remaining
[2021-11-02 09:47:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:33] Number of windows considered: 1...
[2021-11-02 09:47:33] Bias-correcting 1 members separately...
[2021-11-02 09:47:33] Done.
Validation 15, 7 remaining
[2021-11-02 09:47:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:34] Number of windows considered: 1...
[2021-11-02 09:47:34] Bias-correcting 1 members separately...
[2021-11-02 09:47:34] Done.
Validation 16, 6 remaining
[2021-11-02 09:47:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:35] Number of windows considered: 1...
[2021-11-02 09:47:35] Bias-correcting 1 members separately...
[2021-11-02 09:47:35] Done.
Validation 17, 5 remaining
[2021-11-02 09:47:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:36] Number of windows considered: 1...
[2021-11-02 09:47:36] Bias-correcting 1 members separately...
[2021-11-02 09:47:36] Done.
Validation 18, 4 remaining
[2021-11-02 09:47:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:36] Number of windows considered: 1...
[2021-11-02 09:47:36] Bias-correcting 1 members separately...
[2021-11-02 09:47:37] Done.
Validation 19, 3 remaining
[2021-11-02 09:47:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:37] Number of windows considered: 1...
[2021-11-02 09:47:37] Bias-correcting 1 members separately...
[2021-11-02 09:47:37] Done.
Validation 20, 2 remaining
[2021-11-02 09:47:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:38] Number of windows considered: 1...
[2021-11-02 09:47:38] Bias-correcting 1 members separately...
[2021-11-02 09:47:38] Done.
Validation 21, 1 remaining
[2021-11-02 09:47:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:39] Number of windows considered: 1...
[2021-11-02 09:47:39] Bias-correcting 1 members separately...
[2021-11-02 09:47:39] Done.
Validation 22, 0 remaining
[2021-11-02 09:47:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:40] Number of windows considered: 1...
[2021-11-02 09:47:40] Bias-correcting 1 members separately...
[2021-11-02 09:47:40] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-11-02 09:47:40] Performing annual aggregation...
[2021-11-02 09:47:40] Done.
[2021-11-02 09:47:40] - Computing climatology...
[2021-11-02 09:47:40] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.eqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:47:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:50] Number of windows considered: 1...
[2021-11-02 09:47:50] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:47:50] Done.
Validation 2, 20 remaining
[2021-11-02 09:47:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:51] Number of windows considered: 1...
[2021-11-02 09:47:51] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:47:51] Done.
Validation 3, 19 remaining
[2021-11-02 09:47:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:52] Number of windows considered: 1...
[2021-11-02 09:47:52] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:47:52] Done.
Validation 4, 18 remaining
[2021-11-02 09:47:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:52] Number of windows considered: 1...
[2021-11-02 09:47:52] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:47:52] Done.
Validation 5, 17 remaining
[2021-11-02 09:47:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:53] Number of windows considered: 1...
[2021-11-02 09:47:53] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:47:53] Done.
Validation 6, 16 remaining
[2021-11-02 09:47:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:54] Number of windows considered: 1...
[2021-11-02 09:47:54] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:47:54] Done.
Validation 7, 15 remaining
[2021-11-02 09:47:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:54] Number of windows considered: 1...
[2021-11-02 09:47:54] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:47:54] Done.
Validation 8, 14 remaining
[2021-11-02 09:47:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:55] Number of windows considered: 1...
[2021-11-02 09:47:55] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:47:55] Done.
Validation 9, 13 remaining
[2021-11-02 09:47:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:56] Number of windows considered: 1...
[2021-11-02 09:47:56] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:47:56] Done.
Validation 10, 12 remaining
[2021-11-02 09:47:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:56] Number of windows considered: 1...
[2021-11-02 09:47:56] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:47:56] Done.
Validation 11, 11 remaining
[2021-11-02 09:47:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:57] Number of windows considered: 1...
[2021-11-02 09:47:57] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:47:57] Done.
Validation 12, 10 remaining
[2021-11-02 09:47:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:58] Number of windows considered: 1...
[2021-11-02 09:47:58] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:47:58] Done.
Validation 13, 9 remaining
[2021-11-02 09:47:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:58] Number of windows considered: 1...
[2021-11-02 09:47:58] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:47:58] Done.
Validation 14, 8 remaining
[2021-11-02 09:47:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:47:59] Number of windows considered: 1...
[2021-11-02 09:47:59] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:47:59] Done.
Validation 15, 7 remaining
[2021-11-02 09:48:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:00] Number of windows considered: 1...
[2021-11-02 09:48:00] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:00] Done.
Validation 16, 6 remaining
[2021-11-02 09:48:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:00] Number of windows considered: 1...
[2021-11-02 09:48:00] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:01] Done.
Validation 17, 5 remaining
[2021-11-02 09:48:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:01] Number of windows considered: 1...
[2021-11-02 09:48:01] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:48:01] Done.
Validation 18, 4 remaining
[2021-11-02 09:48:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:02] Number of windows considered: 1...
[2021-11-02 09:48:02] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:48:02] Done.
Validation 19, 3 remaining
[2021-11-02 09:48:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:03] Number of windows considered: 1...
[2021-11-02 09:48:03] Bias-correcting 1 members separately...
[2021-11-02 09:48:03] Done.
Validation 20, 2 remaining
[2021-11-02 09:48:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:03] Number of windows considered: 1...
[2021-11-02 09:48:03] Bias-correcting 1 members separately...
[2021-11-02 09:48:03] Done.
Validation 21, 1 remaining
[2021-11-02 09:48:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:04] Number of windows considered: 1...
[2021-11-02 09:48:04] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:04] Done.
Validation 22, 0 remaining
[2021-11-02 09:48:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:05] Number of windows considered: 1...
[2021-11-02 09:48:05] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:05] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-11-02 09:48:05] Performing annual aggregation...
[2021-11-02 09:48:05] Done.
[2021-11-02 09:48:05] - Computing climatology...
[2021-11-02 09:48:05] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:48:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:12] Number of windows considered: 1...
[2021-11-02 09:48:12] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:12] Done.
Validation 2, 20 remaining
[2021-11-02 09:48:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:13] Number of windows considered: 1...
[2021-11-02 09:48:13] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:13] Done.
Validation 3, 19 remaining
[2021-11-02 09:48:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:14] Number of windows considered: 1...
[2021-11-02 09:48:14] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:14] Done.
Validation 4, 18 remaining
[2021-11-02 09:48:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:15] Number of windows considered: 1...
[2021-11-02 09:48:15] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:15] Done.
Validation 5, 17 remaining
[2021-11-02 09:48:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:15] Number of windows considered: 1...
[2021-11-02 09:48:15] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:15] Done.
Validation 6, 16 remaining
[2021-11-02 09:48:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:16] Number of windows considered: 1...
[2021-11-02 09:48:16] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:16] Done.
Validation 7, 15 remaining
[2021-11-02 09:48:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:17] Number of windows considered: 1...
[2021-11-02 09:48:17] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:17] Done.
Validation 8, 14 remaining
[2021-11-02 09:48:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:18] Number of windows considered: 1...
[2021-11-02 09:48:18] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:18] Done.
Validation 9, 13 remaining
[2021-11-02 09:48:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:18] Number of windows considered: 1...
[2021-11-02 09:48:18] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:18] Done.
Validation 10, 12 remaining
[2021-11-02 09:48:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:19] Number of windows considered: 1...
[2021-11-02 09:48:19] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:19] Done.
Validation 11, 11 remaining
[2021-11-02 09:48:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:20] Number of windows considered: 1...
[2021-11-02 09:48:20] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:20] Done.
Validation 12, 10 remaining
[2021-11-02 09:48:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:21] Number of windows considered: 1...
[2021-11-02 09:48:21] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:21] Done.
Validation 13, 9 remaining
[2021-11-02 09:48:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:21] Number of windows considered: 1...
[2021-11-02 09:48:21] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:22] Done.
Validation 14, 8 remaining
[2021-11-02 09:48:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:22] Number of windows considered: 1...
[2021-11-02 09:48:22] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:22] Done.
Validation 15, 7 remaining
[2021-11-02 09:48:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:23] Number of windows considered: 1...
[2021-11-02 09:48:23] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:23] Done.
Validation 16, 6 remaining
[2021-11-02 09:48:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:24] Number of windows considered: 1...
[2021-11-02 09:48:24] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:24] Done.
Validation 17, 5 remaining
[2021-11-02 09:48:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:25] Number of windows considered: 1...
[2021-11-02 09:48:25] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:48:25] Done.
Validation 18, 4 remaining
[2021-11-02 09:48:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:25] Number of windows considered: 1...
[2021-11-02 09:48:25] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:25] Done.
Validation 19, 3 remaining
[2021-11-02 09:48:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:26] Number of windows considered: 1...
[2021-11-02 09:48:26] Bias-correcting 1 members separately...
[2021-11-02 09:48:26] Done.
Validation 20, 2 remaining
[2021-11-02 09:48:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:27] Number of windows considered: 1...
[2021-11-02 09:48:27] Bias-correcting 1 members separately...
[2021-11-02 09:48:27] Done.
Validation 21, 1 remaining
[2021-11-02 09:48:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:28] Number of windows considered: 1...
[2021-11-02 09:48:28] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:28] Done.
Validation 22, 0 remaining
[2021-11-02 09:48:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:48:29] Number of windows considered: 1...
[2021-11-02 09:48:29] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:48:29] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-11-02 09:48:29] Performing annual aggregation...
[2021-11-02 09:48:29] Done.
[2021-11-02 09:48:29] - Computing climatology...
[2021-11-02 09:48:29] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm2.cl5 <- index.cal.station.cl5
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
PQM-WT5 GPQM2-WT5 EQM-WT5 GPQM-WT5
0.9252709 0.6552923 0.6300890 0.1084045
scores.st3.wt5 <- scores
Complete period (WO WTs)
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
[2021-11-02 09:49:58] Performing annual aggregation...
no non-missing arguments to max; returning -Inf[2021-11-02 09:49:58] Done.
[2021-11-02 09:49:58] - Computing climatology...
[2021-11-02 09:49:58] - Done.
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)
index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
[2021-11-02 09:49:58] Performing annual aggregation...
[2021-11-02 09:49:58] Done.
[2021-11-02 09:49:58] - Computing climatology...
[2021-11-02 09:49:58] - Done.
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "pqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-11-02 09:50:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:10] Number of windows considered: 1...
[2021-11-02 09:50:10] Bias-correcting 1 members separately...
[2021-11-02 09:50:10] Done.
Validation 2, 20 remaining
[2021-11-02 09:50:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:11] Number of windows considered: 1...
[2021-11-02 09:50:11] Bias-correcting 1 members separately...
[2021-11-02 09:50:11] Done.
Validation 3, 19 remaining
[2021-11-02 09:50:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:11] Number of windows considered: 1...
[2021-11-02 09:50:11] Bias-correcting 1 members separately...
[2021-11-02 09:50:11] Done.
Validation 4, 18 remaining
[2021-11-02 09:50:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:12] Number of windows considered: 1...
[2021-11-02 09:50:12] Bias-correcting 1 members separately...
[2021-11-02 09:50:12] Done.
Validation 5, 17 remaining
[2021-11-02 09:50:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:13] Number of windows considered: 1...
[2021-11-02 09:50:13] Bias-correcting 1 members separately...
[2021-11-02 09:50:13] Done.
Validation 6, 16 remaining
[2021-11-02 09:50:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:13] Number of windows considered: 1...
[2021-11-02 09:50:13] Bias-correcting 1 members separately...
[2021-11-02 09:50:13] Done.
Validation 7, 15 remaining
[2021-11-02 09:50:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:14] Number of windows considered: 1...
[2021-11-02 09:50:14] Bias-correcting 1 members separately...
[2021-11-02 09:50:14] Done.
Validation 8, 14 remaining
[2021-11-02 09:50:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:15] Number of windows considered: 1...
[2021-11-02 09:50:15] Bias-correcting 1 members separately...
[2021-11-02 09:50:15] Done.
Validation 9, 13 remaining
[2021-11-02 09:50:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:15] Number of windows considered: 1...
[2021-11-02 09:50:15] Bias-correcting 1 members separately...
[2021-11-02 09:50:15] Done.
Validation 10, 12 remaining
[2021-11-02 09:50:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:16] Number of windows considered: 1...
[2021-11-02 09:50:16] Bias-correcting 1 members separately...
[2021-11-02 09:50:16] Done.
Validation 11, 11 remaining
[2021-11-02 09:50:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:17] Number of windows considered: 1...
[2021-11-02 09:50:17] Bias-correcting 1 members separately...
[2021-11-02 09:50:17] Done.
Validation 12, 10 remaining
[2021-11-02 09:50:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:17] Number of windows considered: 1...
[2021-11-02 09:50:17] Bias-correcting 1 members separately...
[2021-11-02 09:50:17] Done.
Validation 13, 9 remaining
[2021-11-02 09:50:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:18] Number of windows considered: 1...
[2021-11-02 09:50:18] Bias-correcting 1 members separately...
[2021-11-02 09:50:18] Done.
Validation 14, 8 remaining
[2021-11-02 09:50:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:19] Number of windows considered: 1...
[2021-11-02 09:50:19] Bias-correcting 1 members separately...
[2021-11-02 09:50:19] Done.
Validation 15, 7 remaining
[2021-11-02 09:50:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:19] Number of windows considered: 1...
[2021-11-02 09:50:19] Bias-correcting 1 members separately...
[2021-11-02 09:50:19] Done.
Validation 16, 6 remaining
[2021-11-02 09:50:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:20] Number of windows considered: 1...
[2021-11-02 09:50:20] Bias-correcting 1 members separately...
[2021-11-02 09:50:20] Done.
Validation 17, 5 remaining
[2021-11-02 09:50:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:21] Number of windows considered: 1...
[2021-11-02 09:50:21] Bias-correcting 1 members separately...
[2021-11-02 09:50:21] Done.
Validation 18, 4 remaining
[2021-11-02 09:50:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:22] Number of windows considered: 1...
[2021-11-02 09:50:22] Bias-correcting 1 members separately...
[2021-11-02 09:50:22] Done.
Validation 19, 3 remaining
[2021-11-02 09:50:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:22] Number of windows considered: 1...
[2021-11-02 09:50:22] Bias-correcting 1 members separately...
[2021-11-02 09:50:22] Done.
Validation 20, 2 remaining
[2021-11-02 09:50:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:23] Number of windows considered: 1...
[2021-11-02 09:50:23] Bias-correcting 1 members separately...
[2021-11-02 09:50:23] Done.
Validation 21, 1 remaining
[2021-11-02 09:50:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:24] Number of windows considered: 1...
[2021-11-02 09:50:24] Bias-correcting 1 members separately...
[2021-11-02 09:50:24] Done.
Validation 22, 0 remaining
[2021-11-02 09:50:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:24] Number of windows considered: 1...
[2021-11-02 09:50:24] Bias-correcting 1 members separately...
[2021-11-02 09:50:25] Done.
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 09:50:25] Performing annual aggregation...
[2021-11-02 09:50:25] Done.
[2021-11-02 09:50:25] - Computing climatology...
[2021-11-02 09:50:25] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.pqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "eqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-11-02 09:50:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:41] Number of windows considered: 1...
[2021-11-02 09:50:41] Bias-correcting 1 members separately...
[2021-11-02 09:50:41] Done.
Validation 2, 20 remaining
[2021-11-02 09:50:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:42] Number of windows considered: 1...
[2021-11-02 09:50:42] Bias-correcting 1 members separately...
[2021-11-02 09:50:42] Done.
Validation 3, 19 remaining
[2021-11-02 09:50:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:43] Number of windows considered: 1...
[2021-11-02 09:50:43] Bias-correcting 1 members separately...
[2021-11-02 09:50:43] Done.
Validation 4, 18 remaining
[2021-11-02 09:50:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:44] Number of windows considered: 1...
[2021-11-02 09:50:44] Bias-correcting 1 members separately...
[2021-11-02 09:50:44] Done.
Validation 5, 17 remaining
[2021-11-02 09:50:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:45] Number of windows considered: 1...
[2021-11-02 09:50:45] Bias-correcting 1 members separately...
[2021-11-02 09:50:45] Done.
Validation 6, 16 remaining
[2021-11-02 09:50:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:46] Number of windows considered: 1...
[2021-11-02 09:50:46] Bias-correcting 1 members separately...
[2021-11-02 09:50:46] Done.
Validation 7, 15 remaining
[2021-11-02 09:50:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:46] Number of windows considered: 1...
[2021-11-02 09:50:46] Bias-correcting 1 members separately...
[2021-11-02 09:50:47] Done.
Validation 8, 14 remaining
[2021-11-02 09:50:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:47] Number of windows considered: 1...
[2021-11-02 09:50:47] Bias-correcting 1 members separately...
[2021-11-02 09:50:47] Done.
Validation 9, 13 remaining
[2021-11-02 09:50:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:48] Number of windows considered: 1...
[2021-11-02 09:50:48] Bias-correcting 1 members separately...
[2021-11-02 09:50:48] Done.
Validation 10, 12 remaining
[2021-11-02 09:50:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:49] Number of windows considered: 1...
[2021-11-02 09:50:49] Bias-correcting 1 members separately...
[2021-11-02 09:50:49] Done.
Validation 11, 11 remaining
[2021-11-02 09:50:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:50] Number of windows considered: 1...
[2021-11-02 09:50:50] Bias-correcting 1 members separately...
[2021-11-02 09:50:50] Done.
Validation 12, 10 remaining
[2021-11-02 09:50:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:51] Number of windows considered: 1...
[2021-11-02 09:50:51] Bias-correcting 1 members separately...
[2021-11-02 09:50:51] Done.
Validation 13, 9 remaining
[2021-11-02 09:50:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:52] Number of windows considered: 1...
[2021-11-02 09:50:52] Bias-correcting 1 members separately...
[2021-11-02 09:50:52] Done.
Validation 14, 8 remaining
[2021-11-02 09:50:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:53] Number of windows considered: 1...
[2021-11-02 09:50:53] Bias-correcting 1 members separately...
[2021-11-02 09:50:53] Done.
Validation 15, 7 remaining
[2021-11-02 09:50:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:53] Number of windows considered: 1...
[2021-11-02 09:50:53] Bias-correcting 1 members separately...
[2021-11-02 09:50:54] Done.
Validation 16, 6 remaining
[2021-11-02 09:50:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:54] Number of windows considered: 1...
[2021-11-02 09:50:54] Bias-correcting 1 members separately...
[2021-11-02 09:50:54] Done.
Validation 17, 5 remaining
[2021-11-02 09:50:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:55] Number of windows considered: 1...
[2021-11-02 09:50:55] Bias-correcting 1 members separately...
[2021-11-02 09:50:55] Done.
Validation 18, 4 remaining
[2021-11-02 09:50:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:56] Number of windows considered: 1...
[2021-11-02 09:50:56] Bias-correcting 1 members separately...
[2021-11-02 09:50:56] Done.
Validation 19, 3 remaining
[2021-11-02 09:50:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:56] Number of windows considered: 1...
[2021-11-02 09:50:56] Bias-correcting 1 members separately...
[2021-11-02 09:50:56] Done.
Validation 20, 2 remaining
[2021-11-02 09:50:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:57] Number of windows considered: 1...
[2021-11-02 09:50:57] Bias-correcting 1 members separately...
[2021-11-02 09:50:57] Done.
Validation 21, 1 remaining
[2021-11-02 09:50:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:58] Number of windows considered: 1...
[2021-11-02 09:50:58] Bias-correcting 1 members separately...
[2021-11-02 09:50:58] Done.
Validation 22, 0 remaining
[2021-11-02 09:50:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:50:58] Number of windows considered: 1...
[2021-11-02 09:50:58] Bias-correcting 1 members separately...
[2021-11-02 09:50:59] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 09:50:59] Performing annual aggregation...
[2021-11-02 09:50:59] Done.
[2021-11-02 09:50:59] - Computing climatology...
[2021-11-02 09:50:59] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.eqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", cross.val = "loo")
Validation 1, 21 remaining
[2021-11-02 09:51:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:51:51] Number of windows considered: 1...
[2021-11-02 09:51:51] Bias-correcting 1 members separately...
[2021-11-02 09:51:51] Done.
Validation 2, 20 remaining
[2021-11-02 09:51:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:51:52] Number of windows considered: 1...
[2021-11-02 09:51:52] Bias-correcting 1 members separately...
[2021-11-02 09:51:52] Done.
Validation 3, 19 remaining
[2021-11-02 09:51:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:51:53] Number of windows considered: 1...
[2021-11-02 09:51:53] Bias-correcting 1 members separately...
[2021-11-02 09:51:53] Done.
Validation 4, 18 remaining
[2021-11-02 09:51:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:51:54] Number of windows considered: 1...
[2021-11-02 09:51:54] Bias-correcting 1 members separately...
[2021-11-02 09:51:54] Done.
Validation 5, 17 remaining
[2021-11-02 09:51:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:51:54] Number of windows considered: 1...
[2021-11-02 09:51:54] Bias-correcting 1 members separately...
[2021-11-02 09:51:55] Done.
Validation 6, 16 remaining
[2021-11-02 09:51:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:51:55] Number of windows considered: 1...
[2021-11-02 09:51:55] Bias-correcting 1 members separately...
[2021-11-02 09:51:55] Done.
Validation 7, 15 remaining
[2021-11-02 09:51:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:51:56] Number of windows considered: 1...
[2021-11-02 09:51:56] Bias-correcting 1 members separately...
[2021-11-02 09:51:56] Done.
Validation 8, 14 remaining
[2021-11-02 09:51:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:51:57] Number of windows considered: 1...
[2021-11-02 09:51:57] Bias-correcting 1 members separately...
[2021-11-02 09:51:57] Done.
Validation 9, 13 remaining
[2021-11-02 09:51:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:51:58] Number of windows considered: 1...
[2021-11-02 09:51:58] Bias-correcting 1 members separately...
[2021-11-02 09:51:58] Done.
Validation 10, 12 remaining
[2021-11-02 09:51:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:51:59] Number of windows considered: 1...
[2021-11-02 09:51:59] Bias-correcting 1 members separately...
[2021-11-02 09:51:59] Done.
Validation 11, 11 remaining
[2021-11-02 09:52:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:00] Number of windows considered: 1...
[2021-11-02 09:52:00] Bias-correcting 1 members separately...
[2021-11-02 09:52:00] Done.
Validation 12, 10 remaining
[2021-11-02 09:52:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:00] Number of windows considered: 1...
[2021-11-02 09:52:00] Bias-correcting 1 members separately...
[2021-11-02 09:52:01] Done.
Validation 13, 9 remaining
[2021-11-02 09:52:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:01] Number of windows considered: 1...
[2021-11-02 09:52:01] Bias-correcting 1 members separately...
[2021-11-02 09:52:01] Done.
Validation 14, 8 remaining
[2021-11-02 09:52:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:02] Number of windows considered: 1...
[2021-11-02 09:52:02] Bias-correcting 1 members separately...
[2021-11-02 09:52:02] Done.
Validation 15, 7 remaining
[2021-11-02 09:52:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:03] Number of windows considered: 1...
[2021-11-02 09:52:03] Bias-correcting 1 members separately...
[2021-11-02 09:52:03] Done.
Validation 16, 6 remaining
[2021-11-02 09:52:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:04] Number of windows considered: 1...
[2021-11-02 09:52:04] Bias-correcting 1 members separately...
[2021-11-02 09:52:04] Done.
Validation 17, 5 remaining
[2021-11-02 09:52:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:05] Number of windows considered: 1...
[2021-11-02 09:52:05] Bias-correcting 1 members separately...
[2021-11-02 09:52:05] Done.
Validation 18, 4 remaining
[2021-11-02 09:52:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:05] Number of windows considered: 1...
[2021-11-02 09:52:05] Bias-correcting 1 members separately...
[2021-11-02 09:52:06] Done.
Validation 19, 3 remaining
[2021-11-02 09:52:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:06] Number of windows considered: 1...
[2021-11-02 09:52:06] Bias-correcting 1 members separately...
[2021-11-02 09:52:07] Done.
Validation 20, 2 remaining
[2021-11-02 09:52:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:07] Number of windows considered: 1...
[2021-11-02 09:52:07] Bias-correcting 1 members separately...
[2021-11-02 09:52:07] Done.
Validation 21, 1 remaining
[2021-11-02 09:52:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:08] Number of windows considered: 1...
[2021-11-02 09:52:08] Bias-correcting 1 members separately...
[2021-11-02 09:52:08] Done.
Validation 22, 0 remaining
[2021-11-02 09:52:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:09] Number of windows considered: 1...
[2021-11-02 09:52:09] Bias-correcting 1 members separately...
[2021-11-02 09:52:09] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 09:52:10] Performing annual aggregation...
[2021-11-02 09:52:10] Done.
[2021-11-02 09:52:10] - Computing climatology...
[2021-11-02 09:52:10] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", theta = .7, cross.val = "loo")
Validation 1, 21 remaining
[2021-11-02 09:52:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:56] Number of windows considered: 1...
[2021-11-02 09:52:56] Bias-correcting 1 members separately...
[2021-11-02 09:52:56] Done.
Validation 2, 20 remaining
[2021-11-02 09:52:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:56] Number of windows considered: 1...
[2021-11-02 09:52:56] Bias-correcting 1 members separately...
[2021-11-02 09:52:57] Done.
Validation 3, 19 remaining
[2021-11-02 09:52:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:57] Number of windows considered: 1...
[2021-11-02 09:52:57] Bias-correcting 1 members separately...
[2021-11-02 09:52:57] Done.
Validation 4, 18 remaining
[2021-11-02 09:52:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:58] Number of windows considered: 1...
[2021-11-02 09:52:58] Bias-correcting 1 members separately...
[2021-11-02 09:52:58] Done.
Validation 5, 17 remaining
[2021-11-02 09:52:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:52:59] Number of windows considered: 1...
[2021-11-02 09:52:59] Bias-correcting 1 members separately...
[2021-11-02 09:52:59] Done.
Validation 6, 16 remaining
[2021-11-02 09:53:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:00] Number of windows considered: 1...
[2021-11-02 09:53:00] Bias-correcting 1 members separately...
[2021-11-02 09:53:00] Done.
Validation 7, 15 remaining
[2021-11-02 09:53:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:01] Number of windows considered: 1...
[2021-11-02 09:53:01] Bias-correcting 1 members separately...
[2021-11-02 09:53:01] Done.
Validation 8, 14 remaining
[2021-11-02 09:53:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:01] Number of windows considered: 1...
[2021-11-02 09:53:01] Bias-correcting 1 members separately...
[2021-11-02 09:53:02] Done.
Validation 9, 13 remaining
[2021-11-02 09:53:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:02] Number of windows considered: 1...
[2021-11-02 09:53:02] Bias-correcting 1 members separately...
[2021-11-02 09:53:02] Done.
Validation 10, 12 remaining
[2021-11-02 09:53:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:03] Number of windows considered: 1...
[2021-11-02 09:53:03] Bias-correcting 1 members separately...
[2021-11-02 09:53:03] Done.
Validation 11, 11 remaining
[2021-11-02 09:53:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:04] Number of windows considered: 1...
[2021-11-02 09:53:04] Bias-correcting 1 members separately...
[2021-11-02 09:53:04] Done.
Validation 12, 10 remaining
[2021-11-02 09:53:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:05] Number of windows considered: 1...
[2021-11-02 09:53:05] Bias-correcting 1 members separately...
[2021-11-02 09:53:05] Done.
Validation 13, 9 remaining
[2021-11-02 09:53:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:06] Number of windows considered: 1...
[2021-11-02 09:53:06] Bias-correcting 1 members separately...
[2021-11-02 09:53:06] Done.
Validation 14, 8 remaining
[2021-11-02 09:53:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:07] Number of windows considered: 1...
[2021-11-02 09:53:07] Bias-correcting 1 members separately...
[2021-11-02 09:53:07] Done.
Validation 15, 7 remaining
[2021-11-02 09:53:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:07] Number of windows considered: 1...
[2021-11-02 09:53:07] Bias-correcting 1 members separately...
[2021-11-02 09:53:07] Done.
Validation 16, 6 remaining
[2021-11-02 09:53:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:08] Number of windows considered: 1...
[2021-11-02 09:53:08] Bias-correcting 1 members separately...
[2021-11-02 09:53:08] Done.
Validation 17, 5 remaining
[2021-11-02 09:53:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:09] Number of windows considered: 1...
[2021-11-02 09:53:09] Bias-correcting 1 members separately...
[2021-11-02 09:53:09] Done.
Validation 18, 4 remaining
[2021-11-02 09:53:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:09] Number of windows considered: 1...
[2021-11-02 09:53:09] Bias-correcting 1 members separately...
[2021-11-02 09:53:09] Done.
Validation 19, 3 remaining
[2021-11-02 09:53:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:10] Number of windows considered: 1...
[2021-11-02 09:53:10] Bias-correcting 1 members separately...
[2021-11-02 09:53:10] Done.
Validation 20, 2 remaining
[2021-11-02 09:53:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:11] Number of windows considered: 1...
[2021-11-02 09:53:11] Bias-correcting 1 members separately...
[2021-11-02 09:53:11] Done.
Validation 21, 1 remaining
[2021-11-02 09:53:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:12] Number of windows considered: 1...
[2021-11-02 09:53:12] Bias-correcting 1 members separately...
[2021-11-02 09:53:12] Done.
Validation 22, 0 remaining
[2021-11-02 09:53:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:53:12] Number of windows considered: 1...
[2021-11-02 09:53:12] Bias-correcting 1 members separately...
[2021-11-02 09:53:12] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 09:53:13] Performing annual aggregation...
[2021-11-02 09:53:13] Done.
[2021-11-02 09:53:13] - Computing climatology...
[2021-11-02 09:53:13] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm2.complete <- index.cal.station.complete
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.trmm.complete[i]-index.obs.complete[i]),abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
score.trmm <- c()
for (i in c(1:9)) {
score.trmm <- c(score.trmm, norm.vector[[i]][1])
}
score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][2])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][3])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][4])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][5])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
PQM-C GPQM2-C EQM-C TRMM GPQM-C
0.6808822 0.6673356 0.5167799 0.4682503 0.4119850
scores.complete <- scores
paste(names(scores.st3.wt1[1]),names(scores.st3.wt2[1]),names(scores.st3.wt3[1]),names(scores.st3.wt4[1]),names(scores.st3.wt5[2]), names(scores.complete[1]))
[1] "PQM-WT1 GPQM2-WT2 GPQM2-WT3 GPQM-WT4 GPQM2-WT5 PQM-C"
Combination of techniques by WT
cal.station.cl1.pqm <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:56:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:16] Number of windows considered: 1...
[2021-11-02 09:56:16] Bias-correcting 1 members separately...
[2021-11-02 09:56:16] Done.
Validation 2, 20 remaining
[2021-11-02 09:56:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:17] Number of windows considered: 1...
[2021-11-02 09:56:17] Bias-correcting 1 members separately...
[2021-11-02 09:56:17] Done.
Validation 3, 19 remaining
[2021-11-02 09:56:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:18] Number of windows considered: 1...
[2021-11-02 09:56:18] Bias-correcting 1 members separately...
[2021-11-02 09:56:18] Done.
Validation 4, 18 remaining
[2021-11-02 09:56:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:19] Number of windows considered: 1...
[2021-11-02 09:56:19] Bias-correcting 1 members separately...
[2021-11-02 09:56:19] Done.
Validation 5, 17 remaining
[2021-11-02 09:56:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:19] Number of windows considered: 1...
[2021-11-02 09:56:19] Bias-correcting 1 members separately...
[2021-11-02 09:56:19] Done.
Validation 6, 16 remaining
[2021-11-02 09:56:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:20] Number of windows considered: 1...
[2021-11-02 09:56:20] Bias-correcting 1 members separately...
[2021-11-02 09:56:20] Done.
Validation 7, 15 remaining
[2021-11-02 09:56:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:21] Number of windows considered: 1...
[2021-11-02 09:56:21] Bias-correcting 1 members separately...
[2021-11-02 09:56:21] Done.
Validation 8, 14 remaining
[2021-11-02 09:56:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:21] Number of windows considered: 1...
[2021-11-02 09:56:21] Bias-correcting 1 members separately...
[2021-11-02 09:56:21] Done.
Validation 9, 13 remaining
[2021-11-02 09:56:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:22] Number of windows considered: 1...
[2021-11-02 09:56:22] Bias-correcting 1 members separately...
[2021-11-02 09:56:22] Done.
Validation 10, 12 remaining
[2021-11-02 09:56:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:23] Number of windows considered: 1...
[2021-11-02 09:56:23] Bias-correcting 1 members separately...
[2021-11-02 09:56:23] Done.
Validation 11, 11 remaining
[2021-11-02 09:56:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:23] Number of windows considered: 1...
[2021-11-02 09:56:23] Bias-correcting 1 members separately...
[2021-11-02 09:56:23] Done.
Validation 12, 10 remaining
[2021-11-02 09:56:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:24] Number of windows considered: 1...
[2021-11-02 09:56:24] Bias-correcting 1 members separately...
[2021-11-02 09:56:24] Done.
Validation 13, 9 remaining
[2021-11-02 09:56:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:25] Number of windows considered: 1...
[2021-11-02 09:56:25] Bias-correcting 1 members separately...
[2021-11-02 09:56:25] Done.
Validation 14, 8 remaining
[2021-11-02 09:56:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:26] Number of windows considered: 1...
[2021-11-02 09:56:26] Bias-correcting 1 members separately...
[2021-11-02 09:56:26] Done.
Validation 15, 7 remaining
[2021-11-02 09:56:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:26] Number of windows considered: 1...
[2021-11-02 09:56:26] Bias-correcting 1 members separately...
[2021-11-02 09:56:26] Done.
Validation 16, 6 remaining
[2021-11-02 09:56:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:27] Number of windows considered: 1...
[2021-11-02 09:56:27] Bias-correcting 1 members separately...
[2021-11-02 09:56:27] Done.
Validation 17, 5 remaining
[2021-11-02 09:56:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:28] Number of windows considered: 1...
[2021-11-02 09:56:28] Bias-correcting 1 members separately...
[2021-11-02 09:56:28] Done.
Validation 18, 4 remaining
[2021-11-02 09:56:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:29] Number of windows considered: 1...
[2021-11-02 09:56:29] Bias-correcting 1 members separately...
[2021-11-02 09:56:29] Done.
Validation 19, 3 remaining
[2021-11-02 09:56:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:29] Number of windows considered: 1...
[2021-11-02 09:56:29] Bias-correcting 1 members separately...
[2021-11-02 09:56:29] Done.
Validation 20, 2 remaining
[2021-11-02 09:56:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:30] Number of windows considered: 1...
[2021-11-02 09:56:30] Bias-correcting 1 members separately...
[2021-11-02 09:56:30] Done.
Validation 21, 1 remaining
[2021-11-02 09:56:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:31] Number of windows considered: 1...
[2021-11-02 09:56:31] Bias-correcting 1 members separately...
[2021-11-02 09:56:31] Done.
Validation 22, 0 remaining
[2021-11-02 09:56:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:32] Number of windows considered: 1...
[2021-11-02 09:56:32] Bias-correcting 1 members separately...
[2021-11-02 09:56:32] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl1.pqm$Dates$start <- as.POSIXct(cal.station.cl1.pqm$Dates$start,tz = "GMT")
cal.station.cl1.pqm$Dates$end <- as.POSIXct(cal.station.cl1.pqm$Dates$end,tz = "GMT")
cal.station.cl2.gpqm2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm", theta = .7, cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-11-02 09:56:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:33] Number of windows considered: 1...
[2021-11-02 09:56:33] Bias-correcting 1 members separately...
[2021-11-02 09:56:33] Done.
Validation 2, 20 remaining
[2021-11-02 09:56:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:34] Number of windows considered: 1...
[2021-11-02 09:56:34] Bias-correcting 1 members separately...
[2021-11-02 09:56:34] Done.
Validation 3, 19 remaining
[2021-11-02 09:56:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:35] Number of windows considered: 1...
[2021-11-02 09:56:35] Bias-correcting 1 members separately...
[2021-11-02 09:56:35] Done.
Validation 4, 18 remaining
[2021-11-02 09:56:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:35] Number of windows considered: 1...
[2021-11-02 09:56:35] Bias-correcting 1 members separately...
[2021-11-02 09:56:35] Done.
Validation 5, 17 remaining
[2021-11-02 09:56:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:36] Number of windows considered: 1...
[2021-11-02 09:56:36] Bias-correcting 1 members separately...
[2021-11-02 09:56:36] Done.
Validation 6, 16 remaining
[2021-11-02 09:56:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:37] Number of windows considered: 1...
[2021-11-02 09:56:37] Bias-correcting 1 members separately...
[2021-11-02 09:56:37] Done.
Validation 7, 15 remaining
[2021-11-02 09:56:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:38] Number of windows considered: 1...
[2021-11-02 09:56:38] Bias-correcting 1 members separately...
[2021-11-02 09:56:38] Done.
Validation 8, 14 remaining
[2021-11-02 09:56:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:38] Number of windows considered: 1...
[2021-11-02 09:56:38] Bias-correcting 1 members separately...
[2021-11-02 09:56:39] Done.
Validation 9, 13 remaining
[2021-11-02 09:56:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:39] Number of windows considered: 1...
[2021-11-02 09:56:39] Bias-correcting 1 members separately...
[2021-11-02 09:56:39] Done.
Validation 10, 12 remaining
[2021-11-02 09:56:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:40] Number of windows considered: 1...
[2021-11-02 09:56:40] Bias-correcting 1 members separately...
[2021-11-02 09:56:40] Done.
Validation 11, 11 remaining
[2021-11-02 09:56:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:41] Number of windows considered: 1...
[2021-11-02 09:56:41] Bias-correcting 1 members separately...
[2021-11-02 09:56:41] Done.
Validation 12, 10 remaining
[2021-11-02 09:56:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:42] Number of windows considered: 1...
[2021-11-02 09:56:42] Bias-correcting 1 members separately...
[2021-11-02 09:56:42] Done.
Validation 13, 9 remaining
[2021-11-02 09:56:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:42] Number of windows considered: 1...
[2021-11-02 09:56:42] Bias-correcting 1 members separately...
[2021-11-02 09:56:42] Done.
Validation 14, 8 remaining
[2021-11-02 09:56:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:43] Number of windows considered: 1...
[2021-11-02 09:56:43] Bias-correcting 1 members separately...
[2021-11-02 09:56:43] Done.
Validation 15, 7 remaining
[2021-11-02 09:56:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:44] Number of windows considered: 1...
[2021-11-02 09:56:44] Bias-correcting 1 members separately...
[2021-11-02 09:56:44] Done.
Validation 16, 6 remaining
[2021-11-02 09:56:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:44] Number of windows considered: 1...
[2021-11-02 09:56:44] Bias-correcting 1 members separately...
[2021-11-02 09:56:44] Done.
Validation 17, 5 remaining
[2021-11-02 09:56:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:45] Number of windows considered: 1...
[2021-11-02 09:56:45] Bias-correcting 1 members separately...
[2021-11-02 09:56:45] Done.
Validation 18, 4 remaining
[2021-11-02 09:56:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:46] Number of windows considered: 1...
[2021-11-02 09:56:46] Bias-correcting 1 members separately...
[2021-11-02 09:56:46] Done.
Validation 19, 3 remaining
[2021-11-02 09:56:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:46] Number of windows considered: 1...
[2021-11-02 09:56:46] Bias-correcting 1 members separately...
[2021-11-02 09:56:46] Done.
Validation 20, 2 remaining
[2021-11-02 09:56:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:47] Number of windows considered: 1...
[2021-11-02 09:56:47] Bias-correcting 1 members separately...
[2021-11-02 09:56:47] Done.
Validation 21, 1 remaining
[2021-11-02 09:56:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:48] Number of windows considered: 1...
[2021-11-02 09:56:48] Bias-correcting 1 members separately...
[2021-11-02 09:56:48] Done.
Validation 22, 0 remaining
[2021-11-02 09:56:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:48] Number of windows considered: 1...
[2021-11-02 09:56:48] Bias-correcting 1 members separately...
[2021-11-02 09:56:49] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl2.gpqm2$Dates$start <- as.POSIXct(cal.station.cl2.gpqm2$Dates$start,tz = "GMT")
cal.station.cl2.gpqm2$Dates$end <- as.POSIXct(cal.station.cl2.gpqm2$Dates$end,tz = "GMT")
cal.station.cl3.gpqm2 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm", theta = .7, cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-11-02 09:56:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:50] Number of windows considered: 1...
[2021-11-02 09:56:50] Bias-correcting 1 members separately...
[2021-11-02 09:56:50] Done.
Validation 2, 20 remaining
[2021-11-02 09:56:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:51] Number of windows considered: 1...
[2021-11-02 09:56:51] Bias-correcting 1 members separately...
[2021-11-02 09:56:51] Done.
Validation 3, 19 remaining
[2021-11-02 09:56:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:51] Number of windows considered: 1...
[2021-11-02 09:56:51] Bias-correcting 1 members separately...
[2021-11-02 09:56:51] Done.
Validation 4, 18 remaining
[2021-11-02 09:56:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:52] Number of windows considered: 1...
[2021-11-02 09:56:52] Bias-correcting 1 members separately...
[2021-11-02 09:56:52] Done.
Validation 5, 17 remaining
[2021-11-02 09:56:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:53] Number of windows considered: 1...
[2021-11-02 09:56:53] Bias-correcting 1 members separately...
[2021-11-02 09:56:53] Done.
Validation 6, 16 remaining
[2021-11-02 09:56:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:53] Number of windows considered: 1...
[2021-11-02 09:56:53] Bias-correcting 1 members separately...
[2021-11-02 09:56:53] Done.
Validation 7, 15 remaining
[2021-11-02 09:56:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:54] Number of windows considered: 1...
[2021-11-02 09:56:54] Bias-correcting 1 members separately...
[2021-11-02 09:56:54] Done.
Validation 8, 14 remaining
[2021-11-02 09:56:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:55] Number of windows considered: 1...
[2021-11-02 09:56:55] Bias-correcting 1 members separately...
[2021-11-02 09:56:55] Done.
Validation 9, 13 remaining
[2021-11-02 09:56:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:56] Number of windows considered: 1...
[2021-11-02 09:56:56] Bias-correcting 1 members separately...
[2021-11-02 09:56:56] Done.
Validation 10, 12 remaining
[2021-11-02 09:56:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:56] Number of windows considered: 1...
[2021-11-02 09:56:56] Bias-correcting 1 members separately...
[2021-11-02 09:56:56] Done.
Validation 11, 11 remaining
[2021-11-02 09:56:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:57] Number of windows considered: 1...
[2021-11-02 09:56:57] Bias-correcting 1 members separately...
[2021-11-02 09:56:57] Done.
Validation 12, 10 remaining
[2021-11-02 09:56:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:58] Number of windows considered: 1...
[2021-11-02 09:56:58] Bias-correcting 1 members separately...
[2021-11-02 09:56:58] Done.
Validation 13, 9 remaining
[2021-11-02 09:56:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:58] Number of windows considered: 1...
[2021-11-02 09:56:58] Bias-correcting 1 members separately...
[2021-11-02 09:56:58] Done.
Validation 14, 8 remaining
[2021-11-02 09:56:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:56:59] Number of windows considered: 1...
[2021-11-02 09:56:59] Bias-correcting 1 members separately...
[2021-11-02 09:56:59] Done.
Validation 15, 7 remaining
[2021-11-02 09:57:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:00] Number of windows considered: 1...
[2021-11-02 09:57:00] Bias-correcting 1 members separately...
[2021-11-02 09:57:00] Done.
Validation 16, 6 remaining
[2021-11-02 09:57:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:01] Number of windows considered: 1...
[2021-11-02 09:57:01] Bias-correcting 1 members separately...
[2021-11-02 09:57:01] Done.
Validation 17, 5 remaining
[2021-11-02 09:57:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:02] Number of windows considered: 1...
[2021-11-02 09:57:02] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:57:02] Done.
Validation 18, 4 remaining
[2021-11-02 09:57:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:02] Number of windows considered: 1...
[2021-11-02 09:57:02] Bias-correcting 1 members separately...
[2021-11-02 09:57:02] Done.
Validation 19, 3 remaining
[2021-11-02 09:57:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:03] Number of windows considered: 1...
[2021-11-02 09:57:03] Bias-correcting 1 members separately...
[2021-11-02 09:57:03] Done.
Validation 20, 2 remaining
[2021-11-02 09:57:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:03] Number of windows considered: 1...
[2021-11-02 09:57:03] Bias-correcting 1 members separately...
[2021-11-02 09:57:03] Done.
Validation 21, 1 remaining
[2021-11-02 09:57:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:04] Number of windows considered: 1...
[2021-11-02 09:57:04] Bias-correcting 1 members separately...
[2021-11-02 09:57:04] Done.
Validation 22, 0 remaining
[2021-11-02 09:57:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:05] Number of windows considered: 1...
[2021-11-02 09:57:05] Bias-correcting 1 members separately...
[2021-11-02 09:57:05] Done.
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl3.gpqm2$Dates$start <- as.POSIXct(cal.station.cl3.gpqm2$Dates$start,tz = "GMT")
cal.station.cl3.gpqm2$Dates$end <- as.POSIXct(cal.station.cl3.gpqm2$Dates$end,tz = "GMT")
cal.station.cl4.gpqm <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm", wt = T)
[2021-11-02 09:57:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:06] Number of windows considered: 1...
[2021-11-02 09:57:06] Bias-correcting 1 members separately...
[2021-11-02 09:57:06] Done.
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl4.gpqm$Dates$start <- as.POSIXct(cal.station.cl4.gpqm$Dates$start,tz = "GMT")
cal.station.cl4.gpqm$Dates$end <- as.POSIXct(cal.station.cl4.gpqm$Dates$end,tz = "GMT")
cal.station.cl5.gpqm2 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm", theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 09:57:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:07] Number of windows considered: 1...
[2021-11-02 09:57:07] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:07] Done.
Validation 2, 20 remaining
[2021-11-02 09:57:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:08] Number of windows considered: 1...
[2021-11-02 09:57:08] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:08] Done.
Validation 3, 19 remaining
[2021-11-02 09:57:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:09] Number of windows considered: 1...
[2021-11-02 09:57:09] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:09] Done.
Validation 4, 18 remaining
[2021-11-02 09:57:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:09] Number of windows considered: 1...
[2021-11-02 09:57:09] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:09] Done.
Validation 5, 17 remaining
[2021-11-02 09:57:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:10] Number of windows considered: 1...
[2021-11-02 09:57:10] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:10] Done.
Validation 6, 16 remaining
[2021-11-02 09:57:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:11] Number of windows considered: 1...
[2021-11-02 09:57:11] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:11] Done.
Validation 7, 15 remaining
[2021-11-02 09:57:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:11] Number of windows considered: 1...
[2021-11-02 09:57:11] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:11] Done.
Validation 8, 14 remaining
[2021-11-02 09:57:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:12] Number of windows considered: 1...
[2021-11-02 09:57:12] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:12] Done.
Validation 9, 13 remaining
[2021-11-02 09:57:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:13] Number of windows considered: 1...
[2021-11-02 09:57:13] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:13] Done.
Validation 10, 12 remaining
[2021-11-02 09:57:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:13] Number of windows considered: 1...
[2021-11-02 09:57:13] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:13] Done.
Validation 11, 11 remaining
[2021-11-02 09:57:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:14] Number of windows considered: 1...
[2021-11-02 09:57:14] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:14] Done.
Validation 12, 10 remaining
[2021-11-02 09:57:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:15] Number of windows considered: 1...
[2021-11-02 09:57:15] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:15] Done.
Validation 13, 9 remaining
[2021-11-02 09:57:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:16] Number of windows considered: 1...
[2021-11-02 09:57:16] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:16] Done.
Validation 14, 8 remaining
[2021-11-02 09:57:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:16] Number of windows considered: 1...
[2021-11-02 09:57:16] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:16] Done.
Validation 15, 7 remaining
[2021-11-02 09:57:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:17] Number of windows considered: 1...
[2021-11-02 09:57:17] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:17] Done.
Validation 16, 6 remaining
[2021-11-02 09:57:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:18] Number of windows considered: 1...
[2021-11-02 09:57:18] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:18] Done.
Validation 17, 5 remaining
[2021-11-02 09:57:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:18] Number of windows considered: 1...
[2021-11-02 09:57:18] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 09:57:19] Done.
Validation 18, 4 remaining
[2021-11-02 09:57:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:19] Number of windows considered: 1...
[2021-11-02 09:57:19] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:19] Done.
Validation 19, 3 remaining
[2021-11-02 09:57:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:20] Number of windows considered: 1...
[2021-11-02 09:57:20] Bias-correcting 1 members separately...
[2021-11-02 09:57:20] Done.
Validation 20, 2 remaining
[2021-11-02 09:57:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:21] Number of windows considered: 1...
[2021-11-02 09:57:21] Bias-correcting 1 members separately...
[2021-11-02 09:57:21] Done.
Validation 21, 1 remaining
[2021-11-02 09:57:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:21] Number of windows considered: 1...
[2021-11-02 09:57:21] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:21] Done.
Validation 22, 0 remaining
[2021-11-02 09:57:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:57:22] Number of windows considered: 1...
[2021-11-02 09:57:22] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 09:57:22] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl5.gpqm2$Dates$start <- as.POSIXct(cal.station.cl5.gpqm2$Dates$start,tz = "GMT")
cal.station.cl5.gpqm2$Dates$end <- as.POSIXct(cal.station.cl5.gpqm2$Dates$end,tz = "GMT")
idx <- which(!is.na(cal.station.cl1.pqm$Data))
cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl2.gpqm2$Data))
cal.station.cl2.gpqm2 <- subsetDimension(cal.station.cl2.gpqm2, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl3.gpqm2$Data))
cal.station.cl3.gpqm2 <- subsetDimension(cal.station.cl3.gpqm2, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl4.gpqm$Data))
cal.station.cl4.gpqm <- subsetDimension(cal.station.cl4.gpqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl5.gpqm2$Data))
cal.station.cl5.gpqm2 <- subsetDimension(cal.station.cl5.gpqm2, dimension = "time", indices = idx)
wt_conditioned <- bindGrid(cal.station.cl1.pqm, cal.station.cl2.gpqm2, cal.station.cl3.gpqm2,
cal.station.cl4.gpqm, cal.station.cl5.gpqm2, dimension = "time")
attr(wt_conditioned$Data, "dimensions") <- "time"
#cambiar de tipo de biasCorrection y fillGridDates
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "pqm", cross.val = "loo")
Validation 1, 21 remaining
[2021-11-02 09:58:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:09] Number of windows considered: 1...
[2021-11-02 09:58:09] Bias-correcting 1 members separately...
[2021-11-02 09:58:09] Done.
Validation 2, 20 remaining
[2021-11-02 09:58:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:10] Number of windows considered: 1...
[2021-11-02 09:58:10] Bias-correcting 1 members separately...
[2021-11-02 09:58:10] Done.
Validation 3, 19 remaining
[2021-11-02 09:58:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:11] Number of windows considered: 1...
[2021-11-02 09:58:11] Bias-correcting 1 members separately...
[2021-11-02 09:58:11] Done.
Validation 4, 18 remaining
[2021-11-02 09:58:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:11] Number of windows considered: 1...
[2021-11-02 09:58:11] Bias-correcting 1 members separately...
[2021-11-02 09:58:11] Done.
Validation 5, 17 remaining
[2021-11-02 09:58:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:12] Number of windows considered: 1...
[2021-11-02 09:58:12] Bias-correcting 1 members separately...
[2021-11-02 09:58:12] Done.
Validation 6, 16 remaining
[2021-11-02 09:58:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:13] Number of windows considered: 1...
[2021-11-02 09:58:13] Bias-correcting 1 members separately...
[2021-11-02 09:58:13] Done.
Validation 7, 15 remaining
[2021-11-02 09:58:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:14] Number of windows considered: 1...
[2021-11-02 09:58:14] Bias-correcting 1 members separately...
[2021-11-02 09:58:14] Done.
Validation 8, 14 remaining
[2021-11-02 09:58:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:14] Number of windows considered: 1...
[2021-11-02 09:58:15] Bias-correcting 1 members separately...
[2021-11-02 09:58:15] Done.
Validation 9, 13 remaining
[2021-11-02 09:58:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:15] Number of windows considered: 1...
[2021-11-02 09:58:15] Bias-correcting 1 members separately...
[2021-11-02 09:58:15] Done.
Validation 10, 12 remaining
[2021-11-02 09:58:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:16] Number of windows considered: 1...
[2021-11-02 09:58:16] Bias-correcting 1 members separately...
[2021-11-02 09:58:16] Done.
Validation 11, 11 remaining
[2021-11-02 09:58:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:17] Number of windows considered: 1...
[2021-11-02 09:58:17] Bias-correcting 1 members separately...
[2021-11-02 09:58:17] Done.
Validation 12, 10 remaining
[2021-11-02 09:58:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:18] Number of windows considered: 1...
[2021-11-02 09:58:18] Bias-correcting 1 members separately...
[2021-11-02 09:58:18] Done.
Validation 13, 9 remaining
[2021-11-02 09:58:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:19] Number of windows considered: 1...
[2021-11-02 09:58:19] Bias-correcting 1 members separately...
[2021-11-02 09:58:19] Done.
Validation 14, 8 remaining
[2021-11-02 09:58:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:19] Number of windows considered: 1...
[2021-11-02 09:58:19] Bias-correcting 1 members separately...
[2021-11-02 09:58:19] Done.
Validation 15, 7 remaining
[2021-11-02 09:58:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:20] Number of windows considered: 1...
[2021-11-02 09:58:20] Bias-correcting 1 members separately...
[2021-11-02 09:58:20] Done.
Validation 16, 6 remaining
[2021-11-02 09:58:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:21] Number of windows considered: 1...
[2021-11-02 09:58:21] Bias-correcting 1 members separately...
[2021-11-02 09:58:21] Done.
Validation 17, 5 remaining
[2021-11-02 09:58:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:21] Number of windows considered: 1...
[2021-11-02 09:58:21] Bias-correcting 1 members separately...
[2021-11-02 09:58:22] Done.
Validation 18, 4 remaining
[2021-11-02 09:58:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:22] Number of windows considered: 1...
[2021-11-02 09:58:22] Bias-correcting 1 members separately...
[2021-11-02 09:58:22] Done.
Validation 19, 3 remaining
[2021-11-02 09:58:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:23] Number of windows considered: 1...
[2021-11-02 09:58:23] Bias-correcting 1 members separately...
[2021-11-02 09:58:23] Done.
Validation 20, 2 remaining
[2021-11-02 09:58:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:24] Number of windows considered: 1...
[2021-11-02 09:58:24] Bias-correcting 1 members separately...
[2021-11-02 09:58:24] Done.
Validation 21, 1 remaining
[2021-11-02 09:58:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:25] Number of windows considered: 1...
[2021-11-02 09:58:25] Bias-correcting 1 members separately...
[2021-11-02 09:58:25] Done.
Validation 22, 0 remaining
[2021-11-02 09:58:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 09:58:26] Number of windows considered: 1...
[2021-11-02 09:58:26] Bias-correcting 1 members separately...
[2021-11-02 09:58:26] Done.
# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))
index.combinated.rv20max <- MaxReturnValue(wt_conditioned)
[2021-11-02 09:58:40] Performing annual aggregation...
[2021-11-02 09:58:40] Done.
[2021-11-02 09:58:40] - Computing climatology...
[2021-11-02 09:58:40] - Done.
index.combinated <- c(index.combinated, index.combinated.rv20max)
index.pqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.pqm <- c(index.pqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.pqm.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 10:00:30] Performing annual aggregation...
[2021-11-02 10:00:30] Done.
[2021-11-02 10:00:30] - Computing climatology...
[2021-11-02 10:00:30] - Done.
index.pqm<- c(index.pqm ,index.pqm.rv20max)
index.pqm
Skewness SDII R10 R10p R20 R20p P98Wet
5.540977e+00 1.344021e+01 1.254668e-01 2.976781e+04 6.460045e-02 2.279663e+04 7.722330e+01
P98WetAmount RV20_max
6.132408e+03 1.678285e+02
diff.conditioned <- abs(index.obs-index.combinated)
diff.pqm <- abs(index.obs-index.pqm)
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
score.combinated <- c()
for (i in c(1:9)) {
score.combinated <- c(score.combinated, norm.vector[[i]][5])
}
score.combinated <- mean(score.combinated)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
Combined PQM-C GPQM2-C EQM-C GPQM-C
0.7895971 0.5738592 0.5439223 0.4250796 0.3778404
df <- data.frame(index.obs, index.combinated, index.pqm)
colnames(df) <- c("Observation","Conditioned", "GPQM")
format(df, digits = 3, scientific = 5)
bias.df <- data.frame(diff.conditioned, diff.pqm)
colnames(bias.df) <- c("Bias Conditioned", "Bias PQM")
format(bias.df, digits = 3, scientific = 5)
df.st1 <- df
bias.df.st1 <- bias.df
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100
names(bias.rel.cond) <- names(diff.conditioned)
bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100
names(bias.rel.no.cond) <- names(diff.conditioned)
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)
colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias GPQM")
format(bias.rel.df, digits = 3, scientific = 5)
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))
abline(a = 0, b = 1)
station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))
points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))
idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))
station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)
points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)
legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))
grid()

Raoul Island, New Zealand
i=4
station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
[2021-10-29 17:02:04] Performing annual aggregation...
[2021-10-29 17:02:04] Done.
[2021-10-29 17:02:04] - Computing climatology...
[2021-10-29 17:02:04] - Done.
index.obs <- c(index.obs, index.obs.rv20max)
index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
[2021-10-29 17:02:04] Performing annual aggregation...
[2021-10-29 17:02:04] Done.
[2021-10-29 17:02:04] - Computing climatology...
[2021-10-29 17:02:04] - Done.
index.trmm <- c(index.trmm, index.trmm.rv20max)
WT1
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))
station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
[2021-10-29 17:02:04] Performing annual aggregation...
[2021-10-29 17:02:04] Done.
[2021-10-29 17:02:04] - Computing climatology...
[2021-10-29 17:02:04] - Done.
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)
index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
[2021-10-29 17:02:04] Performing annual aggregation...
[2021-10-29 17:02:04] Done.
[2021-10-29 17:02:04] - Computing climatology...
[2021-10-29 17:02:04] - Done.
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")
station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "pqm",cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:02:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:06] Number of windows considered: 1...
[2021-10-29 17:02:06] Bias-correcting 1 members separately...
[2021-10-29 17:02:06] Done.
Validation 2, 20 remaining
[2021-10-29 17:02:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:07] Number of windows considered: 1...
[2021-10-29 17:02:07] Bias-correcting 1 members separately...
[2021-10-29 17:02:07] Done.
Validation 3, 19 remaining
[2021-10-29 17:02:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:08] Number of windows considered: 1...
[2021-10-29 17:02:08] Bias-correcting 1 members separately...
[2021-10-29 17:02:08] Done.
Validation 4, 18 remaining
[2021-10-29 17:02:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:08] Number of windows considered: 1...
[2021-10-29 17:02:08] Bias-correcting 1 members separately...
[2021-10-29 17:02:08] Done.
Validation 5, 17 remaining
[2021-10-29 17:02:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:09] Number of windows considered: 1...
[2021-10-29 17:02:09] Bias-correcting 1 members separately...
[2021-10-29 17:02:09] Done.
Validation 6, 16 remaining
[2021-10-29 17:02:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:10] Number of windows considered: 1...
[2021-10-29 17:02:10] Bias-correcting 1 members separately...
[2021-10-29 17:02:10] Done.
Validation 7, 15 remaining
[2021-10-29 17:02:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:11] Number of windows considered: 1...
[2021-10-29 17:02:11] Bias-correcting 1 members separately...
[2021-10-29 17:02:11] Done.
Validation 8, 14 remaining
[2021-10-29 17:02:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:12] Number of windows considered: 1...
[2021-10-29 17:02:12] Bias-correcting 1 members separately...
[2021-10-29 17:02:12] Done.
Validation 9, 13 remaining
[2021-10-29 17:02:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:13] Number of windows considered: 1...
[2021-10-29 17:02:13] Bias-correcting 1 members separately...
[2021-10-29 17:02:13] Done.
Validation 10, 12 remaining
[2021-10-29 17:02:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:14] Number of windows considered: 1...
[2021-10-29 17:02:14] Bias-correcting 1 members separately...
[2021-10-29 17:02:14] Done.
Validation 11, 11 remaining
[2021-10-29 17:02:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:14] Number of windows considered: 1...
[2021-10-29 17:02:14] Bias-correcting 1 members separately...
[2021-10-29 17:02:14] Done.
Validation 12, 10 remaining
[2021-10-29 17:02:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:15] Number of windows considered: 1...
[2021-10-29 17:02:15] Bias-correcting 1 members separately...
[2021-10-29 17:02:15] Done.
Validation 13, 9 remaining
[2021-10-29 17:02:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:16] Number of windows considered: 1...
[2021-10-29 17:02:16] Bias-correcting 1 members separately...
[2021-10-29 17:02:16] Done.
Validation 14, 8 remaining
[2021-10-29 17:02:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:17] Number of windows considered: 1...
[2021-10-29 17:02:17] Bias-correcting 1 members separately...
[2021-10-29 17:02:17] Done.
Validation 15, 7 remaining
[2021-10-29 17:02:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:18] Number of windows considered: 1...
[2021-10-29 17:02:18] Bias-correcting 1 members separately...
[2021-10-29 17:02:18] Done.
Validation 16, 6 remaining
[2021-10-29 17:02:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:19] Number of windows considered: 1...
[2021-10-29 17:02:19] Bias-correcting 1 members separately...
[2021-10-29 17:02:19] Done.
Validation 17, 5 remaining
[2021-10-29 17:02:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:20] Number of windows considered: 1...
[2021-10-29 17:02:20] Bias-correcting 1 members separately...
[2021-10-29 17:02:20] Done.
Validation 18, 4 remaining
[2021-10-29 17:02:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:20] Number of windows considered: 1...
[2021-10-29 17:02:20] Bias-correcting 1 members separately...
[2021-10-29 17:02:21] Done.
Validation 19, 3 remaining
[2021-10-29 17:02:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:21] Number of windows considered: 1...
[2021-10-29 17:02:21] Bias-correcting 1 members separately...
[2021-10-29 17:02:21] Done.
Validation 20, 2 remaining
[2021-10-29 17:02:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:22] Number of windows considered: 1...
[2021-10-29 17:02:22] Bias-correcting 1 members separately...
[2021-10-29 17:02:22] Done.
Validation 21, 1 remaining
[2021-10-29 17:02:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:23] Number of windows considered: 1...
[2021-10-29 17:02:23] Bias-correcting 1 members separately...
[2021-10-29 17:02:23] Done.
Validation 22, 0 remaining
[2021-10-29 17:02:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:24] Number of windows considered: 1...
[2021-10-29 17:02:24] Bias-correcting 1 members separately...
[2021-10-29 17:02:24] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 17:02:25] Performing annual aggregation...
[2021-10-29 17:02:25] Done.
[2021-10-29 17:02:25] - Computing climatology...
[2021-10-29 17:02:25] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.pqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:02:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:26] Number of windows considered: 1...
[2021-10-29 17:02:26] Bias-correcting 1 members separately...
[2021-10-29 17:02:26] Done.
Validation 2, 20 remaining
[2021-10-29 17:02:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:27] Number of windows considered: 1...
[2021-10-29 17:02:27] Bias-correcting 1 members separately...
[2021-10-29 17:02:27] Done.
Validation 3, 19 remaining
[2021-10-29 17:02:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:28] Number of windows considered: 1...
[2021-10-29 17:02:28] Bias-correcting 1 members separately...
[2021-10-29 17:02:28] Done.
Validation 4, 18 remaining
[2021-10-29 17:02:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:29] Number of windows considered: 1...
[2021-10-29 17:02:29] Bias-correcting 1 members separately...
[2021-10-29 17:02:29] Done.
Validation 5, 17 remaining
[2021-10-29 17:02:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:30] Number of windows considered: 1...
[2021-10-29 17:02:30] Bias-correcting 1 members separately...
[2021-10-29 17:02:30] Done.
Validation 6, 16 remaining
[2021-10-29 17:02:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:31] Number of windows considered: 1...
[2021-10-29 17:02:31] Bias-correcting 1 members separately...
[2021-10-29 17:02:31] Done.
Validation 7, 15 remaining
[2021-10-29 17:02:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:32] Number of windows considered: 1...
[2021-10-29 17:02:32] Bias-correcting 1 members separately...
[2021-10-29 17:02:32] Done.
Validation 8, 14 remaining
[2021-10-29 17:02:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:33] Number of windows considered: 1...
[2021-10-29 17:02:33] Bias-correcting 1 members separately...
[2021-10-29 17:02:33] Done.
Validation 9, 13 remaining
[2021-10-29 17:02:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:34] Number of windows considered: 1...
[2021-10-29 17:02:34] Bias-correcting 1 members separately...
[2021-10-29 17:02:34] Done.
Validation 10, 12 remaining
[2021-10-29 17:02:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:35] Number of windows considered: 1...
[2021-10-29 17:02:35] Bias-correcting 1 members separately...
[2021-10-29 17:02:35] Done.
Validation 11, 11 remaining
[2021-10-29 17:02:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:36] Number of windows considered: 1...
[2021-10-29 17:02:36] Bias-correcting 1 members separately...
[2021-10-29 17:02:36] Done.
Validation 12, 10 remaining
[2021-10-29 17:02:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:37] Number of windows considered: 1...
[2021-10-29 17:02:37] Bias-correcting 1 members separately...
[2021-10-29 17:02:37] Done.
Validation 13, 9 remaining
[2021-10-29 17:02:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:38] Number of windows considered: 1...
[2021-10-29 17:02:38] Bias-correcting 1 members separately...
[2021-10-29 17:02:39] Done.
Validation 14, 8 remaining
[2021-10-29 17:02:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:39] Number of windows considered: 1...
[2021-10-29 17:02:40] Bias-correcting 1 members separately...
[2021-10-29 17:02:40] Done.
Validation 15, 7 remaining
[2021-10-29 17:02:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:40] Number of windows considered: 1...
[2021-10-29 17:02:40] Bias-correcting 1 members separately...
[2021-10-29 17:02:41] Done.
Validation 16, 6 remaining
[2021-10-29 17:02:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:42] Number of windows considered: 1...
[2021-10-29 17:02:42] Bias-correcting 1 members separately...
[2021-10-29 17:02:42] Done.
Validation 17, 5 remaining
[2021-10-29 17:02:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:43] Number of windows considered: 1...
[2021-10-29 17:02:43] Bias-correcting 1 members separately...
[2021-10-29 17:02:43] Done.
Validation 18, 4 remaining
[2021-10-29 17:02:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:43] Number of windows considered: 1...
[2021-10-29 17:02:43] Bias-correcting 1 members separately...
[2021-10-29 17:02:44] Done.
Validation 19, 3 remaining
[2021-10-29 17:02:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:44] Number of windows considered: 1...
[2021-10-29 17:02:44] Bias-correcting 1 members separately...
[2021-10-29 17:02:45] Done.
Validation 20, 2 remaining
[2021-10-29 17:02:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:46] Number of windows considered: 1...
[2021-10-29 17:02:46] Bias-correcting 1 members separately...
[2021-10-29 17:02:46] Done.
Validation 21, 1 remaining
[2021-10-29 17:02:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:47] Number of windows considered: 1...
[2021-10-29 17:02:47] Bias-correcting 1 members separately...
[2021-10-29 17:02:47] Done.
Validation 22, 0 remaining
[2021-10-29 17:02:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:48] Number of windows considered: 1...
[2021-10-29 17:02:48] Bias-correcting 1 members separately...
[2021-10-29 17:02:48] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 17:02:49] Performing annual aggregation...
[2021-10-29 17:02:49] Done.
[2021-10-29 17:02:49] - Computing climatology...
[2021-10-29 17:02:49] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.eqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:02:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:50] Number of windows considered: 1...
[2021-10-29 17:02:50] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:02:50] Done.
Validation 2, 20 remaining
[2021-10-29 17:02:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:51] Number of windows considered: 1...
[2021-10-29 17:02:51] Bias-correcting 1 members separately...
[2021-10-29 17:02:51] Done.
Validation 3, 19 remaining
[2021-10-29 17:02:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:52] Number of windows considered: 1...
[2021-10-29 17:02:52] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:02:52] Done.
Validation 4, 18 remaining
[2021-10-29 17:02:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:53] Number of windows considered: 1...
[2021-10-29 17:02:53] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:02:53] Done.
Validation 5, 17 remaining
[2021-10-29 17:02:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:54] Number of windows considered: 1...
[2021-10-29 17:02:54] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:02:54] Done.
Validation 6, 16 remaining
[2021-10-29 17:02:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:55] Number of windows considered: 1...
[2021-10-29 17:02:55] Bias-correcting 1 members separately...
[2021-10-29 17:02:55] Done.
Validation 7, 15 remaining
[2021-10-29 17:02:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:56] Number of windows considered: 1...
[2021-10-29 17:02:56] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:02:56] Done.
Validation 8, 14 remaining
[2021-10-29 17:02:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:57] Number of windows considered: 1...
[2021-10-29 17:02:57] Bias-correcting 1 members separately...
[2021-10-29 17:02:57] Done.
Validation 9, 13 remaining
[2021-10-29 17:02:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:58] Number of windows considered: 1...
[2021-10-29 17:02:58] Bias-correcting 1 members separately...
[2021-10-29 17:02:58] Done.
Validation 10, 12 remaining
[2021-10-29 17:02:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:02:59] Number of windows considered: 1...
[2021-10-29 17:02:59] Bias-correcting 1 members separately...
[2021-10-29 17:02:59] Done.
Validation 11, 11 remaining
[2021-10-29 17:03:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:00] Number of windows considered: 1...
[2021-10-29 17:03:00] Bias-correcting 1 members separately...
[2021-10-29 17:03:00] Done.
Validation 12, 10 remaining
[2021-10-29 17:03:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:01] Number of windows considered: 1...
[2021-10-29 17:03:01] Bias-correcting 1 members separately...
[2021-10-29 17:03:01] Done.
Validation 13, 9 remaining
[2021-10-29 17:03:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:02] Number of windows considered: 1...
[2021-10-29 17:03:02] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:03:02] Done.
Validation 14, 8 remaining
[2021-10-29 17:03:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:03] Number of windows considered: 1...
[2021-10-29 17:03:03] Bias-correcting 1 members separately...
[2021-10-29 17:03:03] Done.
Validation 15, 7 remaining
[2021-10-29 17:03:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:04] Number of windows considered: 1...
[2021-10-29 17:03:04] Bias-correcting 1 members separately...
[2021-10-29 17:03:04] Done.
Validation 16, 6 remaining
[2021-10-29 17:03:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:05] Number of windows considered: 1...
[2021-10-29 17:03:05] Bias-correcting 1 members separately...
[2021-10-29 17:03:05] Done.
Validation 17, 5 remaining
[2021-10-29 17:03:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:06] Number of windows considered: 1...
[2021-10-29 17:03:06] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:03:06] Done.
Validation 18, 4 remaining
[2021-10-29 17:03:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:07] Number of windows considered: 1...
[2021-10-29 17:03:07] Bias-correcting 1 members separately...
[2021-10-29 17:03:07] Done.
Validation 19, 3 remaining
[2021-10-29 17:03:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:08] Number of windows considered: 1...
[2021-10-29 17:03:08] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:03:08] Done.
Validation 20, 2 remaining
[2021-10-29 17:03:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:09] Number of windows considered: 1...
[2021-10-29 17:03:09] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:03:09] Done.
Validation 21, 1 remaining
[2021-10-29 17:03:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:10] Number of windows considered: 1...
[2021-10-29 17:03:10] Bias-correcting 1 members separately...
[2021-10-29 17:03:11] Done.
Validation 22, 0 remaining
[2021-10-29 17:03:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:12] Number of windows considered: 1...
[2021-10-29 17:03:12] Bias-correcting 1 members separately...
[2021-10-29 17:03:12] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 17:03:12] Performing annual aggregation...
[2021-10-29 17:03:12] Done.
[2021-10-29 17:03:12] - Computing climatology...
[2021-10-29 17:03:12] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo' , wt = T)
Validation 1, 21 remaining
[2021-10-29 17:03:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:14] Number of windows considered: 1...
[2021-10-29 17:03:14] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:14] Done.
Validation 2, 20 remaining
[2021-10-29 17:03:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:15] Number of windows considered: 1...
[2021-10-29 17:03:15] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:15] Done.
Validation 3, 19 remaining
[2021-10-29 17:03:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:16] Number of windows considered: 1...
[2021-10-29 17:03:16] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:03:16] Done.
Validation 4, 18 remaining
[2021-10-29 17:03:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:17] Number of windows considered: 1...
[2021-10-29 17:03:17] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:17] Done.
Validation 5, 17 remaining
[2021-10-29 17:03:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:18] Number of windows considered: 1...
[2021-10-29 17:03:18] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:18] Done.
Validation 6, 16 remaining
[2021-10-29 17:03:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:19] Number of windows considered: 1...
[2021-10-29 17:03:19] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:19] Done.
Validation 7, 15 remaining
[2021-10-29 17:03:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:20] Number of windows considered: 1...
[2021-10-29 17:03:20] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:03:20] Done.
Validation 8, 14 remaining
[2021-10-29 17:03:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:21] Number of windows considered: 1...
[2021-10-29 17:03:21] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:21] Done.
Validation 9, 13 remaining
[2021-10-29 17:03:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:22] Number of windows considered: 1...
[2021-10-29 17:03:22] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:22] Done.
Validation 10, 12 remaining
[2021-10-29 17:03:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:24] Number of windows considered: 1...
[2021-10-29 17:03:24] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:24] Done.
Validation 11, 11 remaining
[2021-10-29 17:03:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:24] Number of windows considered: 1...
[2021-10-29 17:03:24] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:24] Done.
Validation 12, 10 remaining
[2021-10-29 17:03:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:25] Number of windows considered: 1...
[2021-10-29 17:03:25] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:25] Done.
Validation 13, 9 remaining
[2021-10-29 17:03:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:26] Number of windows considered: 1...
[2021-10-29 17:03:26] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:03:26] Done.
Validation 14, 8 remaining
[2021-10-29 17:03:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:27] Number of windows considered: 1...
[2021-10-29 17:03:27] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:27] Done.
Validation 15, 7 remaining
[2021-10-29 17:03:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:28] Number of windows considered: 1...
[2021-10-29 17:03:28] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:28] Done.
Validation 16, 6 remaining
[2021-10-29 17:03:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:28] Number of windows considered: 1...
[2021-10-29 17:03:28] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:29] Done.
Validation 17, 5 remaining
[2021-10-29 17:03:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:29] Number of windows considered: 1...
[2021-10-29 17:03:29] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:03:29] Done.
Validation 18, 4 remaining
[2021-10-29 17:03:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:30] Number of windows considered: 1...
[2021-10-29 17:03:30] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:30] Done.
Validation 19, 3 remaining
[2021-10-29 17:03:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:31] Number of windows considered: 1...
[2021-10-29 17:03:31] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:03:31] Done.
Validation 20, 2 remaining
[2021-10-29 17:03:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:32] Number of windows considered: 1...
[2021-10-29 17:03:32] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:32] Done.
Validation 21, 1 remaining
[2021-10-29 17:03:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:33] Number of windows considered: 1...
[2021-10-29 17:03:33] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:33] Done.
Validation 22, 0 remaining
[2021-10-29 17:03:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:34] Number of windows considered: 1...
[2021-10-29 17:03:34] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:03:34] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 17:03:34] Performing annual aggregation...
[2021-10-29 17:03:34] Done.
[2021-10-29 17:03:34] - Computing climatology...
[2021-10-29 17:03:34] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm2.cl1 <- index.cal.station.cl1
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i]))
}
normalization <- function(measure){
measure.norm <- c()
#measure must be a vector with the value of a certain measure of different calibrations
for (i in c(1:length(measure))) {
measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
}
return(measure.norm)
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
scores.st4.wt1 <- scores
WT2
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))
station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
[2021-10-29 17:03:35] Performing annual aggregation...
[2021-10-29 17:03:35] Done.
[2021-10-29 17:03:35] - Computing climatology...
[2021-10-29 17:03:35] - Done.
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)
index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
[2021-10-29 17:03:35] Performing annual aggregation...
[2021-10-29 17:03:35] Done.
[2021-10-29 17:03:35] - Computing climatology...
[2021-10-29 17:03:35] - Done.
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")
station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:03:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:37] Number of windows considered: 1...
[2021-10-29 17:03:37] Bias-correcting 1 members separately...
[2021-10-29 17:03:37] Done.
Validation 2, 20 remaining
[2021-10-29 17:03:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:38] Number of windows considered: 1...
[2021-10-29 17:03:38] Bias-correcting 1 members separately...
[2021-10-29 17:03:38] Done.
Validation 3, 19 remaining
[2021-10-29 17:03:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:39] Number of windows considered: 1...
[2021-10-29 17:03:39] Bias-correcting 1 members separately...
[2021-10-29 17:03:39] Done.
Validation 4, 18 remaining
[2021-10-29 17:03:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:40] Number of windows considered: 1...
[2021-10-29 17:03:40] Bias-correcting 1 members separately...
[2021-10-29 17:03:40] Done.
Validation 5, 17 remaining
[2021-10-29 17:03:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:41] Number of windows considered: 1...
[2021-10-29 17:03:41] Bias-correcting 1 members separately...
[2021-10-29 17:03:41] Done.
Validation 6, 16 remaining
[2021-10-29 17:03:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:41] Number of windows considered: 1...
[2021-10-29 17:03:41] Bias-correcting 1 members separately...
[2021-10-29 17:03:41] Done.
Validation 7, 15 remaining
[2021-10-29 17:03:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:42] Number of windows considered: 1...
[2021-10-29 17:03:42] Bias-correcting 1 members separately...
[2021-10-29 17:03:42] Done.
Validation 8, 14 remaining
[2021-10-29 17:03:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:43] Number of windows considered: 1...
[2021-10-29 17:03:43] Bias-correcting 1 members separately...
[2021-10-29 17:03:43] Done.
Validation 9, 13 remaining
[2021-10-29 17:03:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:44] Number of windows considered: 1...
[2021-10-29 17:03:44] Bias-correcting 1 members separately...
[2021-10-29 17:03:44] Done.
Validation 10, 12 remaining
[2021-10-29 17:03:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:45] Number of windows considered: 1...
[2021-10-29 17:03:45] Bias-correcting 1 members separately...
[2021-10-29 17:03:45] Done.
Validation 11, 11 remaining
[2021-10-29 17:03:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:46] Number of windows considered: 1...
[2021-10-29 17:03:46] Bias-correcting 1 members separately...
[2021-10-29 17:03:46] Done.
Validation 12, 10 remaining
[2021-10-29 17:03:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:47] Number of windows considered: 1...
[2021-10-29 17:03:47] Bias-correcting 1 members separately...
[2021-10-29 17:03:47] Done.
Validation 13, 9 remaining
[2021-10-29 17:03:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:47] Number of windows considered: 1...
[2021-10-29 17:03:47] Bias-correcting 1 members separately...
[2021-10-29 17:03:48] Done.
Validation 14, 8 remaining
[2021-10-29 17:03:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:48] Number of windows considered: 1...
[2021-10-29 17:03:48] Bias-correcting 1 members separately...
[2021-10-29 17:03:48] Done.
Validation 15, 7 remaining
[2021-10-29 17:03:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:49] Number of windows considered: 1...
[2021-10-29 17:03:49] Bias-correcting 1 members separately...
[2021-10-29 17:03:49] Done.
Validation 16, 6 remaining
[2021-10-29 17:03:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:50] Number of windows considered: 1...
[2021-10-29 17:03:50] Bias-correcting 1 members separately...
[2021-10-29 17:03:50] Done.
Validation 17, 5 remaining
[2021-10-29 17:03:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:51] Number of windows considered: 1...
[2021-10-29 17:03:51] Bias-correcting 1 members separately...
[2021-10-29 17:03:51] Done.
Validation 18, 4 remaining
[2021-10-29 17:03:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:52] Number of windows considered: 1...
[2021-10-29 17:03:52] Bias-correcting 1 members separately...
[2021-10-29 17:03:52] Done.
Validation 19, 3 remaining
[2021-10-29 17:03:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:53] Number of windows considered: 1...
[2021-10-29 17:03:53] Bias-correcting 1 members separately...
[2021-10-29 17:03:53] Done.
Validation 20, 2 remaining
[2021-10-29 17:03:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:54] Number of windows considered: 1...
[2021-10-29 17:03:54] Bias-correcting 1 members separately...
[2021-10-29 17:03:54] Done.
Validation 21, 1 remaining
[2021-10-29 17:03:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:55] Number of windows considered: 1...
[2021-10-29 17:03:55] Bias-correcting 1 members separately...
[2021-10-29 17:03:55] Done.
Validation 22, 0 remaining
[2021-10-29 17:03:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:56] Number of windows considered: 1...
[2021-10-29 17:03:56] Bias-correcting 1 members separately...
[2021-10-29 17:03:56] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 17:03:56] Performing annual aggregation...
[2021-10-29 17:03:56] Done.
[2021-10-29 17:03:56] - Computing climatology...
[2021-10-29 17:03:56] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.pqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:03:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:58] Number of windows considered: 1...
[2021-10-29 17:03:58] Bias-correcting 1 members separately...
[2021-10-29 17:03:58] Done.
Validation 2, 20 remaining
[2021-10-29 17:03:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:03:59] Number of windows considered: 1...
[2021-10-29 17:03:59] Bias-correcting 1 members separately...
[2021-10-29 17:03:59] Done.
Validation 3, 19 remaining
[2021-10-29 17:04:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:00] Number of windows considered: 1...
[2021-10-29 17:04:00] Bias-correcting 1 members separately...
[2021-10-29 17:04:00] Done.
Validation 4, 18 remaining
[2021-10-29 17:04:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:01] Number of windows considered: 1...
[2021-10-29 17:04:01] Bias-correcting 1 members separately...
[2021-10-29 17:04:01] Done.
Validation 5, 17 remaining
[2021-10-29 17:04:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:02] Number of windows considered: 1...
[2021-10-29 17:04:02] Bias-correcting 1 members separately...
[2021-10-29 17:04:02] Done.
Validation 6, 16 remaining
[2021-10-29 17:04:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:03] Number of windows considered: 1...
[2021-10-29 17:04:03] Bias-correcting 1 members separately...
[2021-10-29 17:04:03] Done.
Validation 7, 15 remaining
[2021-10-29 17:04:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:04] Number of windows considered: 1...
[2021-10-29 17:04:04] Bias-correcting 1 members separately...
[2021-10-29 17:04:04] Done.
Validation 8, 14 remaining
[2021-10-29 17:04:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:05] Number of windows considered: 1...
[2021-10-29 17:04:05] Bias-correcting 1 members separately...
[2021-10-29 17:04:05] Done.
Validation 9, 13 remaining
[2021-10-29 17:04:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:06] Number of windows considered: 1...
[2021-10-29 17:04:06] Bias-correcting 1 members separately...
[2021-10-29 17:04:07] Done.
Validation 10, 12 remaining
[2021-10-29 17:04:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:07] Number of windows considered: 1...
[2021-10-29 17:04:07] Bias-correcting 1 members separately...
[2021-10-29 17:04:08] Done.
Validation 11, 11 remaining
[2021-10-29 17:04:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:08] Number of windows considered: 1...
[2021-10-29 17:04:08] Bias-correcting 1 members separately...
[2021-10-29 17:04:09] Done.
Validation 12, 10 remaining
[2021-10-29 17:04:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:10] Number of windows considered: 1...
[2021-10-29 17:04:10] Bias-correcting 1 members separately...
[2021-10-29 17:04:10] Done.
Validation 13, 9 remaining
[2021-10-29 17:04:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:11] Number of windows considered: 1...
[2021-10-29 17:04:11] Bias-correcting 1 members separately...
[2021-10-29 17:04:11] Done.
Validation 14, 8 remaining
[2021-10-29 17:04:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:12] Number of windows considered: 1...
[2021-10-29 17:04:12] Bias-correcting 1 members separately...
[2021-10-29 17:04:12] Done.
Validation 15, 7 remaining
[2021-10-29 17:04:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:13] Number of windows considered: 1...
[2021-10-29 17:04:13] Bias-correcting 1 members separately...
[2021-10-29 17:04:13] Done.
Validation 16, 6 remaining
[2021-10-29 17:04:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:14] Number of windows considered: 1...
[2021-10-29 17:04:14] Bias-correcting 1 members separately...
[2021-10-29 17:04:14] Done.
Validation 17, 5 remaining
[2021-10-29 17:04:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:15] Number of windows considered: 1...
[2021-10-29 17:04:15] Bias-correcting 1 members separately...
[2021-10-29 17:04:15] Done.
Validation 18, 4 remaining
[2021-10-29 17:04:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:16] Number of windows considered: 1...
[2021-10-29 17:04:16] Bias-correcting 1 members separately...
[2021-10-29 17:04:16] Done.
Validation 19, 3 remaining
[2021-10-29 17:04:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:17] Number of windows considered: 1...
[2021-10-29 17:04:17] Bias-correcting 1 members separately...
[2021-10-29 17:04:17] Done.
Validation 20, 2 remaining
[2021-10-29 17:04:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:18] Number of windows considered: 1...
[2021-10-29 17:04:18] Bias-correcting 1 members separately...
[2021-10-29 17:04:19] Done.
Validation 21, 1 remaining
[2021-10-29 17:04:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:20] Number of windows considered: 1...
[2021-10-29 17:04:20] Bias-correcting 1 members separately...
[2021-10-29 17:04:20] Done.
Validation 22, 0 remaining
[2021-10-29 17:04:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:21] Number of windows considered: 1...
[2021-10-29 17:04:21] Bias-correcting 1 members separately...
[2021-10-29 17:04:21] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 17:04:22] Performing annual aggregation...
[2021-10-29 17:04:22] Done.
[2021-10-29 17:04:22] - Computing climatology...
[2021-10-29 17:04:22] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.eqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:04:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:23] Number of windows considered: 1...
[2021-10-29 17:04:23] Bias-correcting 1 members separately...
[2021-10-29 17:04:23] Done.
Validation 2, 20 remaining
[2021-10-29 17:04:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:24] Number of windows considered: 1...
[2021-10-29 17:04:24] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:04:24] Done.
Validation 3, 19 remaining
[2021-10-29 17:04:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:25] Number of windows considered: 1...
[2021-10-29 17:04:25] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:04:25] Done.
Validation 4, 18 remaining
[2021-10-29 17:04:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:26] Number of windows considered: 1...
[2021-10-29 17:04:26] Bias-correcting 1 members separately...
[2021-10-29 17:04:26] Done.
Validation 5, 17 remaining
[2021-10-29 17:04:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:27] Number of windows considered: 1...
[2021-10-29 17:04:27] Bias-correcting 1 members separately...
[2021-10-29 17:04:27] Done.
Validation 6, 16 remaining
[2021-10-29 17:04:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:28] Number of windows considered: 1...
[2021-10-29 17:04:28] Bias-correcting 1 members separately...
[2021-10-29 17:04:28] Done.
Validation 7, 15 remaining
[2021-10-29 17:04:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:29] Number of windows considered: 1...
[2021-10-29 17:04:29] Bias-correcting 1 members separately...
[2021-10-29 17:04:29] Done.
Validation 8, 14 remaining
[2021-10-29 17:04:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:30] Number of windows considered: 1...
[2021-10-29 17:04:30] Bias-correcting 1 members separately...
[2021-10-29 17:04:30] Done.
Validation 9, 13 remaining
[2021-10-29 17:04:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:31] Number of windows considered: 1...
[2021-10-29 17:04:31] Bias-correcting 1 members separately...
[2021-10-29 17:04:31] Done.
Validation 10, 12 remaining
[2021-10-29 17:04:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:32] Number of windows considered: 1...
[2021-10-29 17:04:32] Bias-correcting 1 members separately...
[2021-10-29 17:04:32] Done.
Validation 11, 11 remaining
[2021-10-29 17:04:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:33] Number of windows considered: 1...
[2021-10-29 17:04:33] Bias-correcting 1 members separately...
[2021-10-29 17:04:33] Done.
Validation 12, 10 remaining
[2021-10-29 17:04:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:33] Number of windows considered: 1...
[2021-10-29 17:04:33] Bias-correcting 1 members separately...
[2021-10-29 17:04:33] Done.
Validation 13, 9 remaining
[2021-10-29 17:04:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:34] Number of windows considered: 1...
[2021-10-29 17:04:34] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:04:34] Done.
Validation 14, 8 remaining
[2021-10-29 17:04:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:35] Number of windows considered: 1...
[2021-10-29 17:04:35] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:04:35] Done.
Validation 15, 7 remaining
[2021-10-29 17:04:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:36] Number of windows considered: 1...
[2021-10-29 17:04:36] Bias-correcting 1 members separately...
[2021-10-29 17:04:36] Done.
Validation 16, 6 remaining
[2021-10-29 17:04:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:37] Number of windows considered: 1...
[2021-10-29 17:04:37] Bias-correcting 1 members separately...
[2021-10-29 17:04:37] Done.
Validation 17, 5 remaining
[2021-10-29 17:04:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:38] Number of windows considered: 1...
[2021-10-29 17:04:38] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:04:38] Done.
Validation 18, 4 remaining
[2021-10-29 17:04:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:39] Number of windows considered: 1...
[2021-10-29 17:04:39] Bias-correcting 1 members separately...
[2021-10-29 17:04:39] Done.
Validation 19, 3 remaining
[2021-10-29 17:04:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:40] Number of windows considered: 1...
[2021-10-29 17:04:40] Bias-correcting 1 members separately...
[2021-10-29 17:04:40] Done.
Validation 20, 2 remaining
[2021-10-29 17:04:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:41] Number of windows considered: 1...
[2021-10-29 17:04:41] Bias-correcting 1 members separately...
[2021-10-29 17:04:41] Done.
Validation 21, 1 remaining
[2021-10-29 17:04:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:42] Number of windows considered: 1...
[2021-10-29 17:04:42] Bias-correcting 1 members separately...
[2021-10-29 17:04:42] Done.
Validation 22, 0 remaining
[2021-10-29 17:04:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:43] Number of windows considered: 1...
[2021-10-29 17:04:43] Bias-correcting 1 members separately...
[2021-10-29 17:04:43] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 17:04:43] Performing annual aggregation...
[2021-10-29 17:04:43] Done.
[2021-10-29 17:04:43] - Computing climatology...
[2021-10-29 17:04:43] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:04:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:44] Number of windows considered: 1...
[2021-10-29 17:04:44] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:04:44] Done.
Validation 2, 20 remaining
[2021-10-29 17:04:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:45] Number of windows considered: 1...
[2021-10-29 17:04:45] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:04:45] Done.
Validation 3, 19 remaining
[2021-10-29 17:04:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:46] Number of windows considered: 1...
[2021-10-29 17:04:46] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:04:46] Done.
Validation 4, 18 remaining
[2021-10-29 17:04:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:47] Number of windows considered: 1...
[2021-10-29 17:04:47] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:04:47] Done.
Validation 5, 17 remaining
[2021-10-29 17:04:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:48] Number of windows considered: 1...
[2021-10-29 17:04:48] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:04:48] Done.
Validation 6, 16 remaining
[2021-10-29 17:04:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:49] Number of windows considered: 1...
[2021-10-29 17:04:49] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:04:49] Done.
Validation 7, 15 remaining
[2021-10-29 17:04:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:50] Number of windows considered: 1...
[2021-10-29 17:04:50] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:04:50] Done.
Validation 8, 14 remaining
[2021-10-29 17:04:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:51] Number of windows considered: 1...
[2021-10-29 17:04:51] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:04:51] Done.
Validation 9, 13 remaining
[2021-10-29 17:04:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:52] Number of windows considered: 1...
[2021-10-29 17:04:52] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:04:52] Done.
Validation 10, 12 remaining
[2021-10-29 17:04:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:53] Number of windows considered: 1...
[2021-10-29 17:04:53] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:04:53] Done.
Validation 11, 11 remaining
[2021-10-29 17:04:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:54] Number of windows considered: 1...
[2021-10-29 17:04:54] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:04:54] Done.
Validation 12, 10 remaining
[2021-10-29 17:04:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:55] Number of windows considered: 1...
[2021-10-29 17:04:55] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:04:55] Done.
Validation 13, 9 remaining
[2021-10-29 17:04:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:56] Number of windows considered: 1...
[2021-10-29 17:04:56] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:04:56] Done.
Validation 14, 8 remaining
[2021-10-29 17:04:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:56] Number of windows considered: 1...
[2021-10-29 17:04:56] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:04:56] Done.
Validation 15, 7 remaining
[2021-10-29 17:04:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:57] Number of windows considered: 1...
[2021-10-29 17:04:57] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:04:57] Done.
Validation 16, 6 remaining
[2021-10-29 17:04:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:58] Number of windows considered: 1...
[2021-10-29 17:04:58] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:04:58] Done.
Validation 17, 5 remaining
[2021-10-29 17:04:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:04:59] Number of windows considered: 1...
[2021-10-29 17:04:59] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:04:59] Done.
Validation 18, 4 remaining
[2021-10-29 17:05:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:00] Number of windows considered: 1...
[2021-10-29 17:05:00] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:05:00] Done.
Validation 19, 3 remaining
[2021-10-29 17:05:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:00] Number of windows considered: 1...
[2021-10-29 17:05:00] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:05:01] Done.
Validation 20, 2 remaining
[2021-10-29 17:05:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:01] Number of windows considered: 1...
[2021-10-29 17:05:01] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:05:01] Done.
Validation 21, 1 remaining
[2021-10-29 17:05:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:02] Number of windows considered: 1...
[2021-10-29 17:05:02] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:05:02] Done.
Validation 22, 0 remaining
[2021-10-29 17:05:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:03] Number of windows considered: 1...
[2021-10-29 17:05:03] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:05:03] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 17:05:04] Performing annual aggregation...
[2021-10-29 17:05:04] Done.
[2021-10-29 17:05:04] - Computing climatology...
[2021-10-29 17:05:04] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm2.cl2 <- index.cal.station.cl2
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores
EQM-WT2 PQM-WT2 GPQM-WT2 GPQM2-WT2
0.7929146 0.6144988 0.4945134 0.2202600
scores.st4.wt2 <- scores
WT3
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))
station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
[2021-10-29 17:05:05] Performing annual aggregation...
[2021-10-29 17:05:05] Done.
[2021-10-29 17:05:05] - Computing climatology...
[2021-10-29 17:05:05] - Done.
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)
index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
[2021-10-29 17:05:05] Performing annual aggregation...
[2021-10-29 17:05:05] Done.
[2021-10-29 17:05:05] - Computing climatology...
[2021-10-29 17:05:05] - Done.
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")
station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:05:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:06] Number of windows considered: 1...
[2021-10-29 17:05:06] Bias-correcting 1 members separately...
[2021-10-29 17:05:06] Done.
Validation 2, 20 remaining
[2021-10-29 17:05:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:07] Number of windows considered: 1...
[2021-10-29 17:05:07] Bias-correcting 1 members separately...
[2021-10-29 17:05:07] Done.
Validation 3, 19 remaining
[2021-10-29 17:05:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:08] Number of windows considered: 1...
[2021-10-29 17:05:08] Bias-correcting 1 members separately...
[2021-10-29 17:05:08] Done.
Validation 4, 18 remaining
[2021-10-29 17:05:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:09] Number of windows considered: 1...
[2021-10-29 17:05:09] Bias-correcting 1 members separately...
[2021-10-29 17:05:09] Done.
Validation 5, 17 remaining
[2021-10-29 17:05:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:10] Number of windows considered: 1...
[2021-10-29 17:05:10] Bias-correcting 1 members separately...
[2021-10-29 17:05:10] Done.
Validation 6, 16 remaining
[2021-10-29 17:05:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:11] Number of windows considered: 1...
[2021-10-29 17:05:11] Bias-correcting 1 members separately...
[2021-10-29 17:05:11] Done.
Validation 7, 15 remaining
[2021-10-29 17:05:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:12] Number of windows considered: 1...
[2021-10-29 17:05:12] Bias-correcting 1 members separately...
[2021-10-29 17:05:12] Done.
Validation 8, 14 remaining
[2021-10-29 17:05:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:13] Number of windows considered: 1...
[2021-10-29 17:05:13] Bias-correcting 1 members separately...
[2021-10-29 17:05:13] Done.
Validation 9, 13 remaining
[2021-10-29 17:05:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:14] Number of windows considered: 1...
[2021-10-29 17:05:14] Bias-correcting 1 members separately...
[2021-10-29 17:05:14] Done.
Validation 10, 12 remaining
[2021-10-29 17:05:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:15] Number of windows considered: 1...
[2021-10-29 17:05:15] Bias-correcting 1 members separately...
[2021-10-29 17:05:15] Done.
Validation 11, 11 remaining
[2021-10-29 17:05:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:16] Number of windows considered: 1...
[2021-10-29 17:05:16] Bias-correcting 1 members separately...
[2021-10-29 17:05:16] Done.
Validation 12, 10 remaining
[2021-10-29 17:05:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:17] Number of windows considered: 1...
[2021-10-29 17:05:17] Bias-correcting 1 members separately...
[2021-10-29 17:05:17] Done.
Validation 13, 9 remaining
[2021-10-29 17:05:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:18] Number of windows considered: 1...
[2021-10-29 17:05:18] Bias-correcting 1 members separately...
[2021-10-29 17:05:18] Done.
Validation 14, 8 remaining
[2021-10-29 17:05:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:19] Number of windows considered: 1...
[2021-10-29 17:05:19] Bias-correcting 1 members separately...
[2021-10-29 17:05:19] Done.
Validation 15, 7 remaining
[2021-10-29 17:05:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:20] Number of windows considered: 1...
[2021-10-29 17:05:20] Bias-correcting 1 members separately...
[2021-10-29 17:05:20] Done.
Validation 16, 6 remaining
[2021-10-29 17:05:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:21] Number of windows considered: 1...
[2021-10-29 17:05:21] Bias-correcting 1 members separately...
[2021-10-29 17:05:21] Done.
Validation 17, 5 remaining
[2021-10-29 17:05:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:22] Number of windows considered: 1...
[2021-10-29 17:05:22] Bias-correcting 1 members separately...
[2021-10-29 17:05:22] Done.
Validation 18, 4 remaining
[2021-10-29 17:05:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:23] Number of windows considered: 1...
[2021-10-29 17:05:23] Bias-correcting 1 members separately...
[2021-10-29 17:05:23] Done.
Validation 19, 3 remaining
[2021-10-29 17:05:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:24] Number of windows considered: 1...
[2021-10-29 17:05:24] Bias-correcting 1 members separately...
[2021-10-29 17:05:24] Done.
Validation 20, 2 remaining
[2021-10-29 17:05:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:25] Number of windows considered: 1...
[2021-10-29 17:05:25] Bias-correcting 1 members separately...
[2021-10-29 17:05:26] Done.
Validation 21, 1 remaining
[2021-10-29 17:05:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:27] Number of windows considered: 1...
[2021-10-29 17:05:27] Bias-correcting 1 members separately...
[2021-10-29 17:05:27] Done.
Validation 22, 0 remaining
[2021-10-29 17:05:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:28] Number of windows considered: 1...
[2021-10-29 17:05:28] Bias-correcting 1 members separately...
[2021-10-29 17:05:28] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 17:05:28] Performing annual aggregation...
[2021-10-29 17:05:28] Done.
[2021-10-29 17:05:28] - Computing climatology...
[2021-10-29 17:05:28] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.pqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:05:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:29] Number of windows considered: 1...
[2021-10-29 17:05:29] Bias-correcting 1 members separately...
[2021-10-29 17:05:30] Done.
Validation 2, 20 remaining
[2021-10-29 17:05:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:31] Number of windows considered: 1...
[2021-10-29 17:05:31] Bias-correcting 1 members separately...
[2021-10-29 17:05:31] Done.
Validation 3, 19 remaining
[2021-10-29 17:05:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:32] Number of windows considered: 1...
[2021-10-29 17:05:32] Bias-correcting 1 members separately...
[2021-10-29 17:05:32] Done.
Validation 4, 18 remaining
[2021-10-29 17:05:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:33] Number of windows considered: 1...
[2021-10-29 17:05:33] Bias-correcting 1 members separately...
[2021-10-29 17:05:33] Done.
Validation 5, 17 remaining
[2021-10-29 17:05:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:34] Number of windows considered: 1...
[2021-10-29 17:05:34] Bias-correcting 1 members separately...
[2021-10-29 17:05:34] Done.
Validation 6, 16 remaining
[2021-10-29 17:05:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:35] Number of windows considered: 1...
[2021-10-29 17:05:35] Bias-correcting 1 members separately...
[2021-10-29 17:05:35] Done.
Validation 7, 15 remaining
[2021-10-29 17:05:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:36] Number of windows considered: 1...
[2021-10-29 17:05:36] Bias-correcting 1 members separately...
[2021-10-29 17:05:36] Done.
Validation 8, 14 remaining
[2021-10-29 17:05:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:37] Number of windows considered: 1...
[2021-10-29 17:05:37] Bias-correcting 1 members separately...
[2021-10-29 17:05:37] Done.
Validation 9, 13 remaining
[2021-10-29 17:05:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:38] Number of windows considered: 1...
[2021-10-29 17:05:38] Bias-correcting 1 members separately...
[2021-10-29 17:05:38] Done.
Validation 10, 12 remaining
[2021-10-29 17:05:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:39] Number of windows considered: 1...
[2021-10-29 17:05:39] Bias-correcting 1 members separately...
[2021-10-29 17:05:39] Done.
Validation 11, 11 remaining
[2021-10-29 17:05:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:40] Number of windows considered: 1...
[2021-10-29 17:05:40] Bias-correcting 1 members separately...
[2021-10-29 17:05:41] Done.
Validation 12, 10 remaining
[2021-10-29 17:05:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:42] Number of windows considered: 1...
[2021-10-29 17:05:42] Bias-correcting 1 members separately...
[2021-10-29 17:05:42] Done.
Validation 13, 9 remaining
[2021-10-29 17:05:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:43] Number of windows considered: 1...
[2021-10-29 17:05:43] Bias-correcting 1 members separately...
[2021-10-29 17:05:43] Done.
Validation 14, 8 remaining
[2021-10-29 17:05:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:44] Number of windows considered: 1...
[2021-10-29 17:05:44] Bias-correcting 1 members separately...
[2021-10-29 17:05:44] Done.
Validation 15, 7 remaining
[2021-10-29 17:05:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:45] Number of windows considered: 1...
[2021-10-29 17:05:45] Bias-correcting 1 members separately...
[2021-10-29 17:05:45] Done.
Validation 16, 6 remaining
[2021-10-29 17:05:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:46] Number of windows considered: 1...
[2021-10-29 17:05:46] Bias-correcting 1 members separately...
[2021-10-29 17:05:46] Done.
Validation 17, 5 remaining
[2021-10-29 17:05:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:47] Number of windows considered: 1...
[2021-10-29 17:05:47] Bias-correcting 1 members separately...
[2021-10-29 17:05:47] Done.
Validation 18, 4 remaining
[2021-10-29 17:05:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:48] Number of windows considered: 1...
[2021-10-29 17:05:48] Bias-correcting 1 members separately...
[2021-10-29 17:05:48] Done.
Validation 19, 3 remaining
[2021-10-29 17:05:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:49] Number of windows considered: 1...
[2021-10-29 17:05:49] Bias-correcting 1 members separately...
[2021-10-29 17:05:49] Done.
Validation 20, 2 remaining
[2021-10-29 17:05:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:50] Number of windows considered: 1...
[2021-10-29 17:05:50] Bias-correcting 1 members separately...
[2021-10-29 17:05:50] Done.
Validation 21, 1 remaining
[2021-10-29 17:05:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:51] Number of windows considered: 1...
[2021-10-29 17:05:51] Bias-correcting 1 members separately...
[2021-10-29 17:05:51] Done.
Validation 22, 0 remaining
[2021-10-29 17:05:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:52] Number of windows considered: 1...
[2021-10-29 17:05:52] Bias-correcting 1 members separately...
[2021-10-29 17:05:52] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 17:05:53] Performing annual aggregation...
[2021-10-29 17:05:53] Done.
[2021-10-29 17:05:53] - Computing climatology...
[2021-10-29 17:05:53] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.eqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:05:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:54] Number of windows considered: 1...
[2021-10-29 17:05:54] Bias-correcting 1 members separately...
[2021-10-29 17:05:54] Done.
Validation 2, 20 remaining
[2021-10-29 17:05:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:55] Number of windows considered: 1...
[2021-10-29 17:05:55] Bias-correcting 1 members separately...
[2021-10-29 17:05:55] Done.
Validation 3, 19 remaining
[2021-10-29 17:05:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:56] Number of windows considered: 1...
[2021-10-29 17:05:56] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:05:56] Done.
Validation 4, 18 remaining
[2021-10-29 17:05:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:57] Number of windows considered: 1...
[2021-10-29 17:05:57] Bias-correcting 1 members separately...
[2021-10-29 17:05:57] Done.
Validation 5, 17 remaining
[2021-10-29 17:05:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:05:59] Number of windows considered: 1...
[2021-10-29 17:05:59] Bias-correcting 1 members separately...
[2021-10-29 17:05:59] Done.
Validation 6, 16 remaining
[2021-10-29 17:06:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:00] Number of windows considered: 1...
[2021-10-29 17:06:00] Bias-correcting 1 members separately...
[2021-10-29 17:06:00] Done.
Validation 7, 15 remaining
[2021-10-29 17:06:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:01] Number of windows considered: 1...
[2021-10-29 17:06:01] Bias-correcting 1 members separately...
[2021-10-29 17:06:01] Done.
Validation 8, 14 remaining
[2021-10-29 17:06:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:02] Number of windows considered: 1...
[2021-10-29 17:06:02] Bias-correcting 1 members separately...
[2021-10-29 17:06:02] Done.
Validation 9, 13 remaining
[2021-10-29 17:06:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:04] Number of windows considered: 1...
[2021-10-29 17:06:04] Bias-correcting 1 members separately...
[2021-10-29 17:06:04] Done.
Validation 10, 12 remaining
[2021-10-29 17:06:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:05] Number of windows considered: 1...
[2021-10-29 17:06:05] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:06:05] Done.
Validation 11, 11 remaining
[2021-10-29 17:06:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:06] Number of windows considered: 1...
[2021-10-29 17:06:06] Bias-correcting 1 members separately...
[2021-10-29 17:06:06] Done.
Validation 12, 10 remaining
[2021-10-29 17:06:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:07] Number of windows considered: 1...
[2021-10-29 17:06:07] Bias-correcting 1 members separately...
[2021-10-29 17:06:07] Done.
Validation 13, 9 remaining
[2021-10-29 17:06:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:09] Number of windows considered: 1...
[2021-10-29 17:06:09] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:06:09] Done.
Validation 14, 8 remaining
[2021-10-29 17:06:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:10] Number of windows considered: 1...
[2021-10-29 17:06:10] Bias-correcting 1 members separately...
[2021-10-29 17:06:10] Done.
Validation 15, 7 remaining
[2021-10-29 17:06:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:10] Number of windows considered: 1...
[2021-10-29 17:06:10] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:06:11] Done.
Validation 16, 6 remaining
[2021-10-29 17:06:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:11] Number of windows considered: 1...
[2021-10-29 17:06:11] Bias-correcting 1 members separately...
[2021-10-29 17:06:11] Done.
Validation 17, 5 remaining
[2021-10-29 17:06:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:12] Number of windows considered: 1...
[2021-10-29 17:06:12] Bias-correcting 1 members separately...
[2021-10-29 17:06:12] Done.
Validation 18, 4 remaining
[2021-10-29 17:06:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:13] Number of windows considered: 1...
[2021-10-29 17:06:13] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:06:13] Done.
Validation 19, 3 remaining
[2021-10-29 17:06:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:14] Number of windows considered: 1...
[2021-10-29 17:06:14] Bias-correcting 1 members separately...
[2021-10-29 17:06:14] Done.
Validation 20, 2 remaining
[2021-10-29 17:06:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:15] Number of windows considered: 1...
[2021-10-29 17:06:15] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:06:15] Done.
Validation 21, 1 remaining
[2021-10-29 17:06:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:16] Number of windows considered: 1...
[2021-10-29 17:06:16] Bias-correcting 1 members separately...
[2021-10-29 17:06:16] Done.
Validation 22, 0 remaining
[2021-10-29 17:06:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:17] Number of windows considered: 1...
[2021-10-29 17:06:17] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:06:17] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 17:06:18] Performing annual aggregation...
[2021-10-29 17:06:18] Done.
[2021-10-29 17:06:18] - Computing climatology...
[2021-10-29 17:06:18] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:06:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:19] Number of windows considered: 1...
[2021-10-29 17:06:19] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:06:19] Done.
Validation 2, 20 remaining
[2021-10-29 17:06:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:20] Number of windows considered: 1...
[2021-10-29 17:06:20] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:06:20] Done.
Validation 3, 19 remaining
[2021-10-29 17:06:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:21] Number of windows considered: 1...
[2021-10-29 17:06:21] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:06:21] Done.
Validation 4, 18 remaining
[2021-10-29 17:06:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:22] Number of windows considered: 1...
[2021-10-29 17:06:22] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:06:22] Done.
Validation 5, 17 remaining
[2021-10-29 17:06:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:23] Number of windows considered: 1...
[2021-10-29 17:06:23] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:06:23] Done.
Validation 6, 16 remaining
[2021-10-29 17:06:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:24] Number of windows considered: 1...
[2021-10-29 17:06:24] Bias-correcting 1 members separately...
[2021-10-29 17:06:24] Done.
Validation 7, 15 remaining
[2021-10-29 17:06:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:25] Number of windows considered: 1...
[2021-10-29 17:06:25] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:06:25] Done.
Validation 8, 14 remaining
[2021-10-29 17:06:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:26] Number of windows considered: 1...
[2021-10-29 17:06:26] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:06:26] Done.
Validation 9, 13 remaining
[2021-10-29 17:06:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:27] Number of windows considered: 1...
[2021-10-29 17:06:27] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:06:27] Done.
Validation 10, 12 remaining
[2021-10-29 17:06:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:28] Number of windows considered: 1...
[2021-10-29 17:06:28] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:06:28] Done.
Validation 11, 11 remaining
[2021-10-29 17:06:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:29] Number of windows considered: 1...
[2021-10-29 17:06:29] Bias-correcting 1 members separately...
[2021-10-29 17:06:30] Done.
Validation 12, 10 remaining
[2021-10-29 17:06:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:30] Number of windows considered: 1...
[2021-10-29 17:06:30] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:06:31] Done.
Validation 13, 9 remaining
[2021-10-29 17:06:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:31] Number of windows considered: 1...
[2021-10-29 17:06:31] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:06:31] Done.
Validation 14, 8 remaining
[2021-10-29 17:06:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:32] Number of windows considered: 1...
[2021-10-29 17:06:32] Bias-correcting 1 members separately...
[2021-10-29 17:06:32] Done.
Validation 15, 7 remaining
[2021-10-29 17:06:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:34] Number of windows considered: 1...
[2021-10-29 17:06:34] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:06:34] Done.
Validation 16, 6 remaining
[2021-10-29 17:06:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:35] Number of windows considered: 1...
[2021-10-29 17:06:35] Bias-correcting 1 members separately...
[2021-10-29 17:06:35] Done.
Validation 17, 5 remaining
[2021-10-29 17:06:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:36] Number of windows considered: 1...
[2021-10-29 17:06:36] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:06:36] Done.
Validation 18, 4 remaining
[2021-10-29 17:06:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:37] Number of windows considered: 1...
[2021-10-29 17:06:37] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:06:37] Done.
Validation 19, 3 remaining
[2021-10-29 17:06:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:38] Number of windows considered: 1...
[2021-10-29 17:06:38] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:06:38] Done.
Validation 20, 2 remaining
[2021-10-29 17:06:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:39] Number of windows considered: 1...
[2021-10-29 17:06:39] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:06:39] Done.
Validation 21, 1 remaining
[2021-10-29 17:06:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:40] Number of windows considered: 1...
[2021-10-29 17:06:40] Bias-correcting 1 members separately...
[2021-10-29 17:06:40] Done.
Validation 22, 0 remaining
[2021-10-29 17:06:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:41] Number of windows considered: 1...
[2021-10-29 17:06:41] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:06:41] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 17:06:41] Performing annual aggregation...
[2021-10-29 17:06:41] Done.
[2021-10-29 17:06:41] - Computing climatology...
[2021-10-29 17:06:41] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm2.cl3 <- index.cal.station.cl3
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
PQM-WT3 EQM-WT3 GPQM-WT3 GPQM2-WT3
0.8810044 0.8513536 0.4839799 0.1201207
scores.st4.wt3 <- scores
WT4
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))
station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
[2021-10-29 17:06:42] Performing annual aggregation...
[2021-10-29 17:06:42] Done.
[2021-10-29 17:06:42] - Computing climatology...
[2021-10-29 17:06:42] - Done.
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)
index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
[2021-10-29 17:06:42] Performing annual aggregation...
[2021-10-29 17:06:42] Done.
[2021-10-29 17:06:42] - Computing climatology...
[2021-10-29 17:06:42] - Done.
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")
station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:06:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:44] Number of windows considered: 1...
[2021-10-29 17:06:44] Bias-correcting 1 members separately...
[2021-10-29 17:06:44] Done.
Validation 2, 20 remaining
[2021-10-29 17:06:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:45] Number of windows considered: 1...
[2021-10-29 17:06:45] Bias-correcting 1 members separately...
[2021-10-29 17:06:45] Done.
Validation 3, 19 remaining
[2021-10-29 17:06:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:46] Number of windows considered: 1...
[2021-10-29 17:06:46] Bias-correcting 1 members separately...
[2021-10-29 17:06:46] Done.
Validation 4, 18 remaining
[2021-10-29 17:06:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:46] Number of windows considered: 1...
[2021-10-29 17:06:46] Bias-correcting 1 members separately...
[2021-10-29 17:06:47] Done.
Validation 5, 17 remaining
[2021-10-29 17:06:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:48] Number of windows considered: 1...
[2021-10-29 17:06:48] Bias-correcting 1 members separately...
[2021-10-29 17:06:48] Done.
Validation 6, 16 remaining
[2021-10-29 17:06:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:49] Number of windows considered: 1...
[2021-10-29 17:06:49] Bias-correcting 1 members separately...
[2021-10-29 17:06:49] Done.
Validation 7, 15 remaining
[2021-10-29 17:06:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:50] Number of windows considered: 1...
[2021-10-29 17:06:50] Bias-correcting 1 members separately...
[2021-10-29 17:06:50] Done.
Validation 8, 14 remaining
[2021-10-29 17:06:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:51] Number of windows considered: 1...
[2021-10-29 17:06:51] Bias-correcting 1 members separately...
[2021-10-29 17:06:51] Done.
Validation 9, 13 remaining
[2021-10-29 17:06:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:52] Number of windows considered: 1...
[2021-10-29 17:06:52] Bias-correcting 1 members separately...
[2021-10-29 17:06:52] Done.
Validation 10, 12 remaining
[2021-10-29 17:06:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:53] Number of windows considered: 1...
[2021-10-29 17:06:53] Bias-correcting 1 members separately...
[2021-10-29 17:06:53] Done.
Validation 11, 11 remaining
[2021-10-29 17:06:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:54] Number of windows considered: 1...
[2021-10-29 17:06:54] Bias-correcting 1 members separately...
[2021-10-29 17:06:54] Done.
Validation 12, 10 remaining
[2021-10-29 17:06:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:55] Number of windows considered: 1...
[2021-10-29 17:06:55] Bias-correcting 1 members separately...
[2021-10-29 17:06:55] Done.
Validation 13, 9 remaining
[2021-10-29 17:06:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:56] Number of windows considered: 1...
[2021-10-29 17:06:56] Bias-correcting 1 members separately...
[2021-10-29 17:06:56] Done.
Validation 14, 8 remaining
[2021-10-29 17:06:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:57] Number of windows considered: 1...
[2021-10-29 17:06:57] Bias-correcting 1 members separately...
[2021-10-29 17:06:57] Done.
Validation 15, 7 remaining
[2021-10-29 17:06:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:58] Number of windows considered: 1...
[2021-10-29 17:06:58] Bias-correcting 1 members separately...
[2021-10-29 17:06:58] Done.
Validation 16, 6 remaining
[2021-10-29 17:06:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:06:59] Number of windows considered: 1...
[2021-10-29 17:06:59] Bias-correcting 1 members separately...
[2021-10-29 17:06:59] Done.
Validation 17, 5 remaining
[2021-10-29 17:07:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:01] Number of windows considered: 1...
[2021-10-29 17:07:01] Bias-correcting 1 members separately...
[2021-10-29 17:07:01] Done.
Validation 18, 4 remaining
[2021-10-29 17:07:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:02] Number of windows considered: 1...
[2021-10-29 17:07:02] Bias-correcting 1 members separately...
[2021-10-29 17:07:02] Done.
Validation 19, 3 remaining
[2021-10-29 17:07:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:03] Number of windows considered: 1...
[2021-10-29 17:07:03] Bias-correcting 1 members separately...
[2021-10-29 17:07:03] Done.
Validation 20, 2 remaining
[2021-10-29 17:07:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:04] Number of windows considered: 1...
[2021-10-29 17:07:04] Bias-correcting 1 members separately...
[2021-10-29 17:07:04] Done.
Validation 21, 1 remaining
[2021-10-29 17:07:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:05] Number of windows considered: 1...
[2021-10-29 17:07:05] Bias-correcting 1 members separately...
[2021-10-29 17:07:05] Done.
Validation 22, 0 remaining
[2021-10-29 17:07:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:06] Number of windows considered: 1...
[2021-10-29 17:07:06] Bias-correcting 1 members separately...
[2021-10-29 17:07:06] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 17:07:07] Performing annual aggregation...
[2021-10-29 17:07:07] Done.
[2021-10-29 17:07:07] - Computing climatology...
[2021-10-29 17:07:07] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.pqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:07:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:08] Number of windows considered: 1...
[2021-10-29 17:07:08] Bias-correcting 1 members separately...
[2021-10-29 17:07:08] Done.
Validation 2, 20 remaining
[2021-10-29 17:07:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:09] Number of windows considered: 1...
[2021-10-29 17:07:09] Bias-correcting 1 members separately...
[2021-10-29 17:07:09] Done.
Validation 3, 19 remaining
[2021-10-29 17:07:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:11] Number of windows considered: 1...
[2021-10-29 17:07:11] Bias-correcting 1 members separately...
[2021-10-29 17:07:11] Done.
Validation 4, 18 remaining
[2021-10-29 17:07:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:12] Number of windows considered: 1...
[2021-10-29 17:07:12] Bias-correcting 1 members separately...
[2021-10-29 17:07:12] Done.
Validation 5, 17 remaining
[2021-10-29 17:07:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:13] Number of windows considered: 1...
[2021-10-29 17:07:13] Bias-correcting 1 members separately...
[2021-10-29 17:07:13] Done.
Validation 6, 16 remaining
[2021-10-29 17:07:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:15] Number of windows considered: 1...
[2021-10-29 17:07:15] Bias-correcting 1 members separately...
[2021-10-29 17:07:15] Done.
Validation 7, 15 remaining
[2021-10-29 17:07:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:16] Number of windows considered: 1...
[2021-10-29 17:07:16] Bias-correcting 1 members separately...
[2021-10-29 17:07:16] Done.
Validation 8, 14 remaining
[2021-10-29 17:07:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:17] Number of windows considered: 1...
[2021-10-29 17:07:17] Bias-correcting 1 members separately...
[2021-10-29 17:07:17] Done.
Validation 9, 13 remaining
[2021-10-29 17:07:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:18] Number of windows considered: 1...
[2021-10-29 17:07:18] Bias-correcting 1 members separately...
[2021-10-29 17:07:18] Done.
Validation 10, 12 remaining
[2021-10-29 17:07:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:19] Number of windows considered: 1...
[2021-10-29 17:07:19] Bias-correcting 1 members separately...
[2021-10-29 17:07:20] Done.
Validation 11, 11 remaining
[2021-10-29 17:07:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:21] Number of windows considered: 1...
[2021-10-29 17:07:21] Bias-correcting 1 members separately...
[2021-10-29 17:07:21] Done.
Validation 12, 10 remaining
[2021-10-29 17:07:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:22] Number of windows considered: 1...
[2021-10-29 17:07:22] Bias-correcting 1 members separately...
[2021-10-29 17:07:22] Done.
Validation 13, 9 remaining
[2021-10-29 17:07:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:23] Number of windows considered: 1...
[2021-10-29 17:07:23] Bias-correcting 1 members separately...
[2021-10-29 17:07:23] Done.
Validation 14, 8 remaining
[2021-10-29 17:07:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:24] Number of windows considered: 1...
[2021-10-29 17:07:24] Bias-correcting 1 members separately...
[2021-10-29 17:07:25] Done.
Validation 15, 7 remaining
[2021-10-29 17:07:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:26] Number of windows considered: 1...
[2021-10-29 17:07:26] Bias-correcting 1 members separately...
[2021-10-29 17:07:26] Done.
Validation 16, 6 remaining
[2021-10-29 17:07:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:28] Number of windows considered: 1...
[2021-10-29 17:07:28] Bias-correcting 1 members separately...
[2021-10-29 17:07:28] Done.
Validation 17, 5 remaining
[2021-10-29 17:07:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:29] Number of windows considered: 1...
[2021-10-29 17:07:29] Bias-correcting 1 members separately...
[2021-10-29 17:07:30] Done.
Validation 18, 4 remaining
[2021-10-29 17:07:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:31] Number of windows considered: 1...
[2021-10-29 17:07:31] Bias-correcting 1 members separately...
[2021-10-29 17:07:32] Done.
Validation 19, 3 remaining
[2021-10-29 17:07:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:34] Number of windows considered: 1...
[2021-10-29 17:07:34] Bias-correcting 1 members separately...
[2021-10-29 17:07:34] Done.
Validation 20, 2 remaining
[2021-10-29 17:07:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:36] Number of windows considered: 1...
[2021-10-29 17:07:36] Bias-correcting 1 members separately...
[2021-10-29 17:07:36] Done.
Validation 21, 1 remaining
[2021-10-29 17:07:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:38] Number of windows considered: 1...
[2021-10-29 17:07:38] Bias-correcting 1 members separately...
[2021-10-29 17:07:38] Done.
Validation 22, 0 remaining
[2021-10-29 17:07:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:40] Number of windows considered: 1...
[2021-10-29 17:07:40] Bias-correcting 1 members separately...
[2021-10-29 17:07:40] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 17:07:41] Performing annual aggregation...
[2021-10-29 17:07:41] Done.
[2021-10-29 17:07:41] - Computing climatology...
[2021-10-29 17:07:41] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.eqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:07:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:42] Number of windows considered: 1...
[2021-10-29 17:07:42] Bias-correcting 1 members separately...
[2021-10-29 17:07:42] Done.
Validation 2, 20 remaining
[2021-10-29 17:07:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:43] Number of windows considered: 1...
[2021-10-29 17:07:43] Bias-correcting 1 members separately...
[2021-10-29 17:07:43] Done.
Validation 3, 19 remaining
[2021-10-29 17:07:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:45] Number of windows considered: 1...
[2021-10-29 17:07:45] Bias-correcting 1 members separately...
optimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:07:45] Done.
Validation 4, 18 remaining
[2021-10-29 17:07:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:46] Number of windows considered: 1...
[2021-10-29 17:07:46] Bias-correcting 1 members separately...
optimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:07:46] Done.
Validation 5, 17 remaining
[2021-10-29 17:07:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:47] Number of windows considered: 1...
[2021-10-29 17:07:47] Bias-correcting 1 members separately...
optimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:07:47] Done.
Validation 6, 16 remaining
[2021-10-29 17:07:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:48] Number of windows considered: 1...
[2021-10-29 17:07:48] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:07:48] Done.
Validation 7, 15 remaining
[2021-10-29 17:07:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:50] Number of windows considered: 1...
[2021-10-29 17:07:50] Bias-correcting 1 members separately...
[2021-10-29 17:07:50] Done.
Validation 8, 14 remaining
[2021-10-29 17:07:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:51] Number of windows considered: 1...
[2021-10-29 17:07:51] Bias-correcting 1 members separately...
optimization may not have succeeded[2021-10-29 17:07:51] Done.
Validation 9, 13 remaining
[2021-10-29 17:07:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:52] Number of windows considered: 1...
[2021-10-29 17:07:52] Bias-correcting 1 members separately...
optimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:07:52] Done.
Validation 10, 12 remaining
[2021-10-29 17:07:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:54] Number of windows considered: 1...
[2021-10-29 17:07:54] Bias-correcting 1 members separately...
[2021-10-29 17:07:54] Done.
Validation 11, 11 remaining
[2021-10-29 17:07:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:55] Number of windows considered: 1...
[2021-10-29 17:07:55] Bias-correcting 1 members separately...
optimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:07:55] Done.
Validation 12, 10 remaining
[2021-10-29 17:07:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:56] Number of windows considered: 1...
[2021-10-29 17:07:56] Bias-correcting 1 members separately...
optimization may not have succeeded[2021-10-29 17:07:56] Done.
Validation 13, 9 remaining
[2021-10-29 17:07:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:57] Number of windows considered: 1...
[2021-10-29 17:07:57] Bias-correcting 1 members separately...
optimization may not have succeeded[2021-10-29 17:07:57] Done.
Validation 14, 8 remaining
[2021-10-29 17:07:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:58] Number of windows considered: 1...
[2021-10-29 17:07:58] Bias-correcting 1 members separately...
[2021-10-29 17:07:58] Done.
Validation 15, 7 remaining
[2021-10-29 17:07:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:07:59] Number of windows considered: 1...
[2021-10-29 17:07:59] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:07:59] Done.
Validation 16, 6 remaining
[2021-10-29 17:08:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:00] Number of windows considered: 1...
[2021-10-29 17:08:00] Bias-correcting 1 members separately...
[2021-10-29 17:08:00] Done.
Validation 17, 5 remaining
[2021-10-29 17:08:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:01] Number of windows considered: 1...
[2021-10-29 17:08:01] Bias-correcting 1 members separately...
optimization may not have succeeded[2021-10-29 17:08:01] Done.
Validation 18, 4 remaining
[2021-10-29 17:08:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:02] Number of windows considered: 1...
[2021-10-29 17:08:02] Bias-correcting 1 members separately...
optimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:08:02] Done.
Validation 19, 3 remaining
[2021-10-29 17:08:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:03] Number of windows considered: 1...
[2021-10-29 17:08:03] Bias-correcting 1 members separately...
[2021-10-29 17:08:03] Done.
Validation 20, 2 remaining
[2021-10-29 17:08:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:04] Number of windows considered: 1...
[2021-10-29 17:08:04] Bias-correcting 1 members separately...
[2021-10-29 17:08:04] Done.
Validation 21, 1 remaining
[2021-10-29 17:08:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:05] Number of windows considered: 1...
[2021-10-29 17:08:05] Bias-correcting 1 members separately...
[2021-10-29 17:08:05] Done.
Validation 22, 0 remaining
[2021-10-29 17:08:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:06] Number of windows considered: 1...
[2021-10-29 17:08:06] Bias-correcting 1 members separately...
optimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:08:06] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 17:08:06] Performing annual aggregation...
[2021-10-29 17:08:06] Done.
[2021-10-29 17:08:06] - Computing climatology...
[2021-10-29 17:08:06] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:08:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:07] Number of windows considered: 1...
[2021-10-29 17:08:07] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:07] Done.
Validation 2, 20 remaining
[2021-10-29 17:08:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:08] Number of windows considered: 1...
[2021-10-29 17:08:08] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:08] Done.
Validation 3, 19 remaining
[2021-10-29 17:08:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:10] Number of windows considered: 1...
[2021-10-29 17:08:10] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:10] Done.
Validation 4, 18 remaining
[2021-10-29 17:08:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:11] Number of windows considered: 1...
[2021-10-29 17:08:11] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:11] Done.
Validation 5, 17 remaining
[2021-10-29 17:08:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:12] Number of windows considered: 1...
[2021-10-29 17:08:12] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:12] Done.
Validation 6, 16 remaining
[2021-10-29 17:08:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:13] Number of windows considered: 1...
[2021-10-29 17:08:13] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:13] Done.
Validation 7, 15 remaining
[2021-10-29 17:08:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:14] Number of windows considered: 1...
[2021-10-29 17:08:14] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:14] Done.
Validation 8, 14 remaining
[2021-10-29 17:08:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:15] Number of windows considered: 1...
[2021-10-29 17:08:15] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:15] Done.
Validation 9, 13 remaining
[2021-10-29 17:08:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:16] Number of windows considered: 1...
[2021-10-29 17:08:16] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:16] Done.
Validation 10, 12 remaining
[2021-10-29 17:08:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:17] Number of windows considered: 1...
[2021-10-29 17:08:17] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:17] Done.
Validation 11, 11 remaining
[2021-10-29 17:08:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:18] Number of windows considered: 1...
[2021-10-29 17:08:18] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:18] Done.
Validation 12, 10 remaining
[2021-10-29 17:08:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:19] Number of windows considered: 1...
[2021-10-29 17:08:19] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:19] Done.
Validation 13, 9 remaining
[2021-10-29 17:08:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:20] Number of windows considered: 1...
[2021-10-29 17:08:20] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:20] Done.
Validation 14, 8 remaining
[2021-10-29 17:08:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:21] Number of windows considered: 1...
[2021-10-29 17:08:21] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:21] Done.
Validation 15, 7 remaining
[2021-10-29 17:08:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:22] Number of windows considered: 1...
[2021-10-29 17:08:22] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:22] Done.
Validation 16, 6 remaining
[2021-10-29 17:08:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:23] Number of windows considered: 1...
[2021-10-29 17:08:23] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:23] Done.
Validation 17, 5 remaining
[2021-10-29 17:08:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:24] Number of windows considered: 1...
[2021-10-29 17:08:24] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:24] Done.
Validation 18, 4 remaining
[2021-10-29 17:08:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:25] Number of windows considered: 1...
[2021-10-29 17:08:25] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:25] Done.
Validation 19, 3 remaining
[2021-10-29 17:08:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:26] Number of windows considered: 1...
[2021-10-29 17:08:26] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:26] Done.
Validation 20, 2 remaining
[2021-10-29 17:08:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:27] Number of windows considered: 1...
[2021-10-29 17:08:27] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:08:27] Done.
Validation 21, 1 remaining
[2021-10-29 17:08:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:28] Number of windows considered: 1...
[2021-10-29 17:08:28] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:28] Done.
Validation 22, 0 remaining
[2021-10-29 17:08:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:29] Number of windows considered: 1...
[2021-10-29 17:08:29] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:08:29] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 17:08:30] Performing annual aggregation...
[2021-10-29 17:08:30] Done.
[2021-10-29 17:08:30] - Computing climatology...
[2021-10-29 17:08:30] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm2.cl4 <- index.cal.station.cl4
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)
scores
EQM-WT4 GPQM2-WT4 PQM-WT4 GPQM-WT4
0.8419517 0.5961061 0.4580815 0.4331912
scores.st4.wt4 <- scores
WT5
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))
station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
[2021-10-29 17:08:31] Performing annual aggregation...
no non-missing arguments to max; returning -Inf[2021-10-29 17:08:31] Done.
[2021-10-29 17:08:31] - Computing climatology...
[2021-10-29 17:08:31] - Done.
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)
index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
[2021-10-29 17:08:31] Performing annual aggregation...
[2021-10-29 17:08:31] Done.
[2021-10-29 17:08:31] - Computing climatology...
[2021-10-29 17:08:31] - Done.
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")
station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:08:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:32] Number of windows considered: 1...
[2021-10-29 17:08:32] Bias-correcting 1 members separately...
[2021-10-29 17:08:32] Done.
Validation 2, 20 remaining
[2021-10-29 17:08:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:33] Number of windows considered: 1...
[2021-10-29 17:08:33] Bias-correcting 1 members separately...
[2021-10-29 17:08:33] Done.
Validation 3, 19 remaining
[2021-10-29 17:08:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:34] Number of windows considered: 1...
[2021-10-29 17:08:34] Bias-correcting 1 members separately...
[2021-10-29 17:08:34] Done.
Validation 4, 18 remaining
[2021-10-29 17:08:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:35] Number of windows considered: 1...
[2021-10-29 17:08:35] Bias-correcting 1 members separately...
[2021-10-29 17:08:35] Done.
Validation 5, 17 remaining
[2021-10-29 17:08:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:36] Number of windows considered: 1...
[2021-10-29 17:08:36] Bias-correcting 1 members separately...
[2021-10-29 17:08:36] Done.
Validation 6, 16 remaining
[2021-10-29 17:08:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:37] Number of windows considered: 1...
[2021-10-29 17:08:37] Bias-correcting 1 members separately...
[2021-10-29 17:08:37] Done.
Validation 7, 15 remaining
[2021-10-29 17:08:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:38] Number of windows considered: 1...
[2021-10-29 17:08:38] Bias-correcting 1 members separately...
[2021-10-29 17:08:38] Done.
Validation 8, 14 remaining
[2021-10-29 17:08:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:39] Number of windows considered: 1...
[2021-10-29 17:08:39] Bias-correcting 1 members separately...
[2021-10-29 17:08:39] Done.
Validation 9, 13 remaining
[2021-10-29 17:08:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:40] Number of windows considered: 1...
[2021-10-29 17:08:40] Bias-correcting 1 members separately...
[2021-10-29 17:08:40] Done.
Validation 10, 12 remaining
[2021-10-29 17:08:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:41] Number of windows considered: 1...
[2021-10-29 17:08:41] Bias-correcting 1 members separately...
[2021-10-29 17:08:41] Done.
Validation 11, 11 remaining
[2021-10-29 17:08:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:42] Number of windows considered: 1...
[2021-10-29 17:08:42] Bias-correcting 1 members separately...
[2021-10-29 17:08:42] Done.
Validation 12, 10 remaining
[2021-10-29 17:08:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:43] Number of windows considered: 1...
[2021-10-29 17:08:43] Bias-correcting 1 members separately...
[2021-10-29 17:08:43] Done.
Validation 13, 9 remaining
[2021-10-29 17:08:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:45] Number of windows considered: 1...
[2021-10-29 17:08:45] Bias-correcting 1 members separately...
[2021-10-29 17:08:45] Done.
Validation 14, 8 remaining
[2021-10-29 17:08:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:46] Number of windows considered: 1...
[2021-10-29 17:08:46] Bias-correcting 1 members separately...
[2021-10-29 17:08:46] Done.
Validation 15, 7 remaining
[2021-10-29 17:08:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:47] Number of windows considered: 1...
[2021-10-29 17:08:47] Bias-correcting 1 members separately...
[2021-10-29 17:08:47] Done.
Validation 16, 6 remaining
[2021-10-29 17:08:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:48] Number of windows considered: 1...
[2021-10-29 17:08:48] Bias-correcting 1 members separately...
[2021-10-29 17:08:48] Done.
Validation 17, 5 remaining
[2021-10-29 17:08:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:49] Number of windows considered: 1...
[2021-10-29 17:08:49] Bias-correcting 1 members separately...
[2021-10-29 17:08:49] Done.
Validation 18, 4 remaining
[2021-10-29 17:08:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:50] Number of windows considered: 1...
[2021-10-29 17:08:50] Bias-correcting 1 members separately...
[2021-10-29 17:08:50] Done.
Validation 19, 3 remaining
[2021-10-29 17:08:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:51] Number of windows considered: 1...
[2021-10-29 17:08:51] Bias-correcting 1 members separately...
[2021-10-29 17:08:51] Done.
Validation 20, 2 remaining
[2021-10-29 17:08:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:52] Number of windows considered: 1...
[2021-10-29 17:08:52] Bias-correcting 1 members separately...
[2021-10-29 17:08:52] Done.
Validation 21, 1 remaining
[2021-10-29 17:08:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:53] Number of windows considered: 1...
[2021-10-29 17:08:53] Bias-correcting 1 members separately...
[2021-10-29 17:08:53] Done.
Validation 22, 0 remaining
[2021-10-29 17:08:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:54] Number of windows considered: 1...
[2021-10-29 17:08:54] Bias-correcting 1 members separately...
[2021-10-29 17:08:54] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 17:08:55] Performing annual aggregation...
[2021-10-29 17:08:55] Done.
[2021-10-29 17:08:55] - Computing climatology...
[2021-10-29 17:08:55] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.pqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:08:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:56] Number of windows considered: 1...
[2021-10-29 17:08:56] Bias-correcting 1 members separately...
[2021-10-29 17:08:56] Done.
Validation 2, 20 remaining
[2021-10-29 17:08:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:58] Number of windows considered: 1...
[2021-10-29 17:08:58] Bias-correcting 1 members separately...
[2021-10-29 17:08:58] Done.
Validation 3, 19 remaining
[2021-10-29 17:08:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:08:59] Number of windows considered: 1...
[2021-10-29 17:08:59] Bias-correcting 1 members separately...
[2021-10-29 17:08:59] Done.
Validation 4, 18 remaining
[2021-10-29 17:09:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:00] Number of windows considered: 1...
[2021-10-29 17:09:00] Bias-correcting 1 members separately...
[2021-10-29 17:09:00] Done.
Validation 5, 17 remaining
[2021-10-29 17:09:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:01] Number of windows considered: 1...
[2021-10-29 17:09:01] Bias-correcting 1 members separately...
[2021-10-29 17:09:01] Done.
Validation 6, 16 remaining
[2021-10-29 17:09:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:02] Number of windows considered: 1...
[2021-10-29 17:09:02] Bias-correcting 1 members separately...
[2021-10-29 17:09:03] Done.
Validation 7, 15 remaining
[2021-10-29 17:09:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:04] Number of windows considered: 1...
[2021-10-29 17:09:04] Bias-correcting 1 members separately...
[2021-10-29 17:09:04] Done.
Validation 8, 14 remaining
[2021-10-29 17:09:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:05] Number of windows considered: 1...
[2021-10-29 17:09:05] Bias-correcting 1 members separately...
[2021-10-29 17:09:05] Done.
Validation 9, 13 remaining
[2021-10-29 17:09:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:06] Number of windows considered: 1...
[2021-10-29 17:09:06] Bias-correcting 1 members separately...
[2021-10-29 17:09:06] Done.
Validation 10, 12 remaining
[2021-10-29 17:09:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:08] Number of windows considered: 1...
[2021-10-29 17:09:08] Bias-correcting 1 members separately...
[2021-10-29 17:09:08] Done.
Validation 11, 11 remaining
[2021-10-29 17:09:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:09] Number of windows considered: 1...
[2021-10-29 17:09:09] Bias-correcting 1 members separately...
[2021-10-29 17:09:09] Done.
Validation 12, 10 remaining
[2021-10-29 17:09:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:10] Number of windows considered: 1...
[2021-10-29 17:09:10] Bias-correcting 1 members separately...
[2021-10-29 17:09:10] Done.
Validation 13, 9 remaining
[2021-10-29 17:09:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:11] Number of windows considered: 1...
[2021-10-29 17:09:11] Bias-correcting 1 members separately...
[2021-10-29 17:09:11] Done.
Validation 14, 8 remaining
[2021-10-29 17:09:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:12] Number of windows considered: 1...
[2021-10-29 17:09:12] Bias-correcting 1 members separately...
[2021-10-29 17:09:13] Done.
Validation 15, 7 remaining
[2021-10-29 17:09:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:14] Number of windows considered: 1...
[2021-10-29 17:09:14] Bias-correcting 1 members separately...
[2021-10-29 17:09:14] Done.
Validation 16, 6 remaining
[2021-10-29 17:09:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:15] Number of windows considered: 1...
[2021-10-29 17:09:15] Bias-correcting 1 members separately...
[2021-10-29 17:09:15] Done.
Validation 17, 5 remaining
[2021-10-29 17:09:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:16] Number of windows considered: 1...
[2021-10-29 17:09:16] Bias-correcting 1 members separately...
[2021-10-29 17:09:16] Done.
Validation 18, 4 remaining
[2021-10-29 17:09:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:18] Number of windows considered: 1...
[2021-10-29 17:09:18] Bias-correcting 1 members separately...
[2021-10-29 17:09:18] Done.
Validation 19, 3 remaining
[2021-10-29 17:09:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:19] Number of windows considered: 1...
[2021-10-29 17:09:19] Bias-correcting 1 members separately...
[2021-10-29 17:09:19] Done.
Validation 20, 2 remaining
[2021-10-29 17:09:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:20] Number of windows considered: 1...
[2021-10-29 17:09:20] Bias-correcting 1 members separately...
[2021-10-29 17:09:20] Done.
Validation 21, 1 remaining
[2021-10-29 17:09:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:21] Number of windows considered: 1...
[2021-10-29 17:09:21] Bias-correcting 1 members separately...
[2021-10-29 17:09:21] Done.
Validation 22, 0 remaining
[2021-10-29 17:09:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:23] Number of windows considered: 1...
[2021-10-29 17:09:23] Bias-correcting 1 members separately...
[2021-10-29 17:09:23] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 17:09:23] Performing annual aggregation...
[2021-10-29 17:09:23] Done.
[2021-10-29 17:09:23] - Computing climatology...
[2021-10-29 17:09:23] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.eqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:09:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:25] Number of windows considered: 1...
[2021-10-29 17:09:25] Bias-correcting 1 members separately...
[2021-10-29 17:09:25] Done.
Validation 2, 20 remaining
[2021-10-29 17:09:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:26] Number of windows considered: 1...
[2021-10-29 17:09:26] Bias-correcting 1 members separately...
[2021-10-29 17:09:26] Done.
Validation 3, 19 remaining
[2021-10-29 17:09:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:27] Number of windows considered: 1...
[2021-10-29 17:09:27] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:09:27] Done.
Validation 4, 18 remaining
[2021-10-29 17:09:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:28] Number of windows considered: 1...
[2021-10-29 17:09:28] Bias-correcting 1 members separately...
[2021-10-29 17:09:29] Done.
Validation 5, 17 remaining
[2021-10-29 17:09:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:30] Number of windows considered: 1...
[2021-10-29 17:09:30] Bias-correcting 1 members separately...
[2021-10-29 17:09:30] Done.
Validation 6, 16 remaining
[2021-10-29 17:09:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:31] Number of windows considered: 1...
[2021-10-29 17:09:31] Bias-correcting 1 members separately...
[2021-10-29 17:09:31] Done.
Validation 7, 15 remaining
[2021-10-29 17:09:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:33] Number of windows considered: 1...
[2021-10-29 17:09:33] Bias-correcting 1 members separately...
[2021-10-29 17:09:33] Done.
Validation 8, 14 remaining
[2021-10-29 17:09:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:34] Number of windows considered: 1...
[2021-10-29 17:09:34] Bias-correcting 1 members separately...
[2021-10-29 17:09:34] Done.
Validation 9, 13 remaining
[2021-10-29 17:09:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:34] Number of windows considered: 1...
[2021-10-29 17:09:34] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:09:35] Done.
Validation 10, 12 remaining
[2021-10-29 17:09:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:35] Number of windows considered: 1...
[2021-10-29 17:09:35] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:09:36] Done.
Validation 11, 11 remaining
[2021-10-29 17:09:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:36] Number of windows considered: 1...
[2021-10-29 17:09:36] Bias-correcting 1 members separately...
[2021-10-29 17:09:37] Done.
Validation 12, 10 remaining
[2021-10-29 17:09:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:37] Number of windows considered: 1...
[2021-10-29 17:09:37] Bias-correcting 1 members separately...
[2021-10-29 17:09:38] Done.
Validation 13, 9 remaining
[2021-10-29 17:09:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:38] Number of windows considered: 1...
[2021-10-29 17:09:38] Bias-correcting 1 members separately...
[2021-10-29 17:09:39] Done.
Validation 14, 8 remaining
[2021-10-29 17:09:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:39] Number of windows considered: 1...
[2021-10-29 17:09:39] Bias-correcting 1 members separately...
[2021-10-29 17:09:40] Done.
Validation 15, 7 remaining
[2021-10-29 17:09:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:40] Number of windows considered: 1...
[2021-10-29 17:09:40] Bias-correcting 1 members separately...
[2021-10-29 17:09:40] Done.
Validation 16, 6 remaining
[2021-10-29 17:09:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:41] Number of windows considered: 1...
[2021-10-29 17:09:41] Bias-correcting 1 members separately...
[2021-10-29 17:09:41] Done.
Validation 17, 5 remaining
[2021-10-29 17:09:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:42] Number of windows considered: 1...
[2021-10-29 17:09:42] Bias-correcting 1 members separately...
[2021-10-29 17:09:42] Done.
Validation 18, 4 remaining
[2021-10-29 17:09:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:43] Number of windows considered: 1...
[2021-10-29 17:09:43] Bias-correcting 1 members separately...
[2021-10-29 17:09:43] Done.
Validation 19, 3 remaining
[2021-10-29 17:09:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:44] Number of windows considered: 1...
[2021-10-29 17:09:44] Bias-correcting 1 members separately...
[2021-10-29 17:09:44] Done.
Validation 20, 2 remaining
[2021-10-29 17:09:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:45] Number of windows considered: 1...
[2021-10-29 17:09:45] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:09:45] Done.
Validation 21, 1 remaining
[2021-10-29 17:09:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:46] Number of windows considered: 1...
[2021-10-29 17:09:46] Bias-correcting 1 members separately...
[2021-10-29 17:09:46] Done.
Validation 22, 0 remaining
[2021-10-29 17:09:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:47] Number of windows considered: 1...
[2021-10-29 17:09:47] Bias-correcting 1 members separately...
[2021-10-29 17:09:48] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 17:09:48] Performing annual aggregation...
[2021-10-29 17:09:48] Done.
[2021-10-29 17:09:48] - Computing climatology...
[2021-10-29 17:09:48] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:09:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:49] Number of windows considered: 1...
[2021-10-29 17:09:49] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:09:50] Done.
Validation 2, 20 remaining
[2021-10-29 17:09:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:50] Number of windows considered: 1...
[2021-10-29 17:09:50] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:09:51] Done.
Validation 3, 19 remaining
[2021-10-29 17:09:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:52] Number of windows considered: 1...
[2021-10-29 17:09:52] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:09:52] Done.
Validation 4, 18 remaining
[2021-10-29 17:09:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:52] Number of windows considered: 1...
[2021-10-29 17:09:52] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:09:53] Done.
Validation 5, 17 remaining
[2021-10-29 17:09:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:53] Number of windows considered: 1...
[2021-10-29 17:09:53] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:09:54] Done.
Validation 6, 16 remaining
[2021-10-29 17:09:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:55] Number of windows considered: 1...
[2021-10-29 17:09:55] Bias-correcting 1 members separately...
[2021-10-29 17:09:55] Done.
Validation 7, 15 remaining
[2021-10-29 17:09:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:56] Number of windows considered: 1...
[2021-10-29 17:09:56] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:09:56] Done.
Validation 8, 14 remaining
[2021-10-29 17:09:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:57] Number of windows considered: 1...
[2021-10-29 17:09:57] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:09:57] Done.
Validation 9, 13 remaining
[2021-10-29 17:09:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:58] Number of windows considered: 1...
[2021-10-29 17:09:58] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:09:58] Done.
Validation 10, 12 remaining
[2021-10-29 17:09:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:09:59] Number of windows considered: 1...
[2021-10-29 17:09:59] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:09:59] Done.
Validation 11, 11 remaining
[2021-10-29 17:10:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:00] Number of windows considered: 1...
[2021-10-29 17:10:00] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:10:00] Done.
Validation 12, 10 remaining
[2021-10-29 17:10:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:01] Number of windows considered: 1...
[2021-10-29 17:10:01] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:10:01] Done.
Validation 13, 9 remaining
[2021-10-29 17:10:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:02] Number of windows considered: 1...
[2021-10-29 17:10:02] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:10:02] Done.
Validation 14, 8 remaining
[2021-10-29 17:10:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:03] Number of windows considered: 1...
[2021-10-29 17:10:03] Bias-correcting 1 members separately...
[2021-10-29 17:10:03] Done.
Validation 15, 7 remaining
[2021-10-29 17:10:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:04] Number of windows considered: 1...
[2021-10-29 17:10:04] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:10:04] Done.
Validation 16, 6 remaining
[2021-10-29 17:10:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:05] Number of windows considered: 1...
[2021-10-29 17:10:05] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:10:05] Done.
Validation 17, 5 remaining
[2021-10-29 17:10:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:06] Number of windows considered: 1...
[2021-10-29 17:10:06] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:10:06] Done.
Validation 18, 4 remaining
[2021-10-29 17:10:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:07] Number of windows considered: 1...
[2021-10-29 17:10:07] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:10:08] Done.
Validation 19, 3 remaining
[2021-10-29 17:10:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:09] Number of windows considered: 1...
[2021-10-29 17:10:09] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:10:09] Done.
Validation 20, 2 remaining
[2021-10-29 17:10:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:10] Number of windows considered: 1...
[2021-10-29 17:10:10] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:10:10] Done.
Validation 21, 1 remaining
[2021-10-29 17:10:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:11] Number of windows considered: 1...
[2021-10-29 17:10:11] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:10:11] Done.
Validation 22, 0 remaining
[2021-10-29 17:10:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:12] Number of windows considered: 1...
[2021-10-29 17:10:12] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:10:12] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 17:10:13] Performing annual aggregation...
[2021-10-29 17:10:13] Done.
[2021-10-29 17:10:13] - Computing climatology...
[2021-10-29 17:10:13] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm2.cl5 <- index.cal.station.cl5
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
EQM-WT5 PQM-WT5 GPQM2-WT5 GPQM-WT5
0.9330717 0.8447921 0.4605535 0.1433480
scores.st4.wt5 <- scores
Complete period (WO WTs)
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
[2021-10-29 17:10:13] Performing annual aggregation...
[2021-10-29 17:10:13] Done.
[2021-10-29 17:10:13] - Computing climatology...
[2021-10-29 17:10:13] - Done.
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)
index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
[2021-10-29 17:10:13] Performing annual aggregation...
[2021-10-29 17:10:13] Done.
[2021-10-29 17:10:13] - Computing climatology...
[2021-10-29 17:10:13] - Done.
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "pqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-10-29 17:10:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:15] Number of windows considered: 1...
[2021-10-29 17:10:15] Bias-correcting 1 members separately...
[2021-10-29 17:10:15] Done.
Validation 2, 20 remaining
[2021-10-29 17:10:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:16] Number of windows considered: 1...
[2021-10-29 17:10:16] Bias-correcting 1 members separately...
[2021-10-29 17:10:16] Done.
Validation 3, 19 remaining
[2021-10-29 17:10:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:17] Number of windows considered: 1...
[2021-10-29 17:10:17] Bias-correcting 1 members separately...
[2021-10-29 17:10:17] Done.
Validation 4, 18 remaining
[2021-10-29 17:10:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:18] Number of windows considered: 1...
[2021-10-29 17:10:18] Bias-correcting 1 members separately...
[2021-10-29 17:10:18] Done.
Validation 5, 17 remaining
[2021-10-29 17:10:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:19] Number of windows considered: 1...
[2021-10-29 17:10:19] Bias-correcting 1 members separately...
[2021-10-29 17:10:19] Done.
Validation 6, 16 remaining
[2021-10-29 17:10:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:20] Number of windows considered: 1...
[2021-10-29 17:10:20] Bias-correcting 1 members separately...
[2021-10-29 17:10:20] Done.
Validation 7, 15 remaining
[2021-10-29 17:10:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:21] Number of windows considered: 1...
[2021-10-29 17:10:21] Bias-correcting 1 members separately...
[2021-10-29 17:10:21] Done.
Validation 8, 14 remaining
[2021-10-29 17:10:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:22] Number of windows considered: 1...
[2021-10-29 17:10:22] Bias-correcting 1 members separately...
[2021-10-29 17:10:22] Done.
Validation 9, 13 remaining
[2021-10-29 17:10:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:23] Number of windows considered: 1...
[2021-10-29 17:10:23] Bias-correcting 1 members separately...
[2021-10-29 17:10:23] Done.
Validation 10, 12 remaining
[2021-10-29 17:10:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:24] Number of windows considered: 1...
[2021-10-29 17:10:24] Bias-correcting 1 members separately...
[2021-10-29 17:10:24] Done.
Validation 11, 11 remaining
[2021-10-29 17:10:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:26] Number of windows considered: 1...
[2021-10-29 17:10:26] Bias-correcting 1 members separately...
[2021-10-29 17:10:26] Done.
Validation 12, 10 remaining
[2021-10-29 17:10:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:27] Number of windows considered: 1...
[2021-10-29 17:10:27] Bias-correcting 1 members separately...
[2021-10-29 17:10:27] Done.
Validation 13, 9 remaining
[2021-10-29 17:10:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:28] Number of windows considered: 1...
[2021-10-29 17:10:28] Bias-correcting 1 members separately...
[2021-10-29 17:10:28] Done.
Validation 14, 8 remaining
[2021-10-29 17:10:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:29] Number of windows considered: 1...
[2021-10-29 17:10:29] Bias-correcting 1 members separately...
[2021-10-29 17:10:29] Done.
Validation 15, 7 remaining
[2021-10-29 17:10:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:30] Number of windows considered: 1...
[2021-10-29 17:10:30] Bias-correcting 1 members separately...
[2021-10-29 17:10:30] Done.
Validation 16, 6 remaining
[2021-10-29 17:10:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:31] Number of windows considered: 1...
[2021-10-29 17:10:31] Bias-correcting 1 members separately...
[2021-10-29 17:10:31] Done.
Validation 17, 5 remaining
[2021-10-29 17:10:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:32] Number of windows considered: 1...
[2021-10-29 17:10:32] Bias-correcting 1 members separately...
[2021-10-29 17:10:33] Done.
Validation 18, 4 remaining
[2021-10-29 17:10:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:34] Number of windows considered: 1...
[2021-10-29 17:10:34] Bias-correcting 1 members separately...
[2021-10-29 17:10:34] Done.
Validation 19, 3 remaining
[2021-10-29 17:10:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:35] Number of windows considered: 1...
[2021-10-29 17:10:35] Bias-correcting 1 members separately...
[2021-10-29 17:10:35] Done.
Validation 20, 2 remaining
[2021-10-29 17:10:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:36] Number of windows considered: 1...
[2021-10-29 17:10:36] Bias-correcting 1 members separately...
[2021-10-29 17:10:36] Done.
Validation 21, 1 remaining
[2021-10-29 17:10:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:37] Number of windows considered: 1...
[2021-10-29 17:10:37] Bias-correcting 1 members separately...
[2021-10-29 17:10:37] Done.
Validation 22, 0 remaining
[2021-10-29 17:10:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:38] Number of windows considered: 1...
[2021-10-29 17:10:38] Bias-correcting 1 members separately...
[2021-10-29 17:10:38] Done.
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:10:39] Performing annual aggregation...
[2021-10-29 17:10:39] Done.
[2021-10-29 17:10:39] - Computing climatology...
[2021-10-29 17:10:39] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.pqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "eqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-10-29 17:10:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:40] Number of windows considered: 1...
[2021-10-29 17:10:40] Bias-correcting 1 members separately...
[2021-10-29 17:10:40] Done.
Validation 2, 20 remaining
[2021-10-29 17:10:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:42] Number of windows considered: 1...
[2021-10-29 17:10:42] Bias-correcting 1 members separately...
[2021-10-29 17:10:42] Done.
Validation 3, 19 remaining
[2021-10-29 17:10:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:43] Number of windows considered: 1...
[2021-10-29 17:10:43] Bias-correcting 1 members separately...
[2021-10-29 17:10:43] Done.
Validation 4, 18 remaining
[2021-10-29 17:10:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:44] Number of windows considered: 1...
[2021-10-29 17:10:44] Bias-correcting 1 members separately...
[2021-10-29 17:10:44] Done.
Validation 5, 17 remaining
[2021-10-29 17:10:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:45] Number of windows considered: 1...
[2021-10-29 17:10:45] Bias-correcting 1 members separately...
[2021-10-29 17:10:45] Done.
Validation 6, 16 remaining
[2021-10-29 17:10:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:46] Number of windows considered: 1...
[2021-10-29 17:10:46] Bias-correcting 1 members separately...
[2021-10-29 17:10:47] Done.
Validation 7, 15 remaining
[2021-10-29 17:10:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:48] Number of windows considered: 1...
[2021-10-29 17:10:48] Bias-correcting 1 members separately...
[2021-10-29 17:10:48] Done.
Validation 8, 14 remaining
[2021-10-29 17:10:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:49] Number of windows considered: 1...
[2021-10-29 17:10:49] Bias-correcting 1 members separately...
[2021-10-29 17:10:49] Done.
Validation 9, 13 remaining
[2021-10-29 17:10:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:50] Number of windows considered: 1...
[2021-10-29 17:10:50] Bias-correcting 1 members separately...
[2021-10-29 17:10:50] Done.
Validation 10, 12 remaining
[2021-10-29 17:10:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:51] Number of windows considered: 1...
[2021-10-29 17:10:51] Bias-correcting 1 members separately...
[2021-10-29 17:10:52] Done.
Validation 11, 11 remaining
[2021-10-29 17:10:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:53] Number of windows considered: 1...
[2021-10-29 17:10:53] Bias-correcting 1 members separately...
[2021-10-29 17:10:53] Done.
Validation 12, 10 remaining
[2021-10-29 17:10:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:54] Number of windows considered: 1...
[2021-10-29 17:10:54] Bias-correcting 1 members separately...
[2021-10-29 17:10:54] Done.
Validation 13, 9 remaining
[2021-10-29 17:10:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:55] Number of windows considered: 1...
[2021-10-29 17:10:55] Bias-correcting 1 members separately...
[2021-10-29 17:10:55] Done.
Validation 14, 8 remaining
[2021-10-29 17:10:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:56] Number of windows considered: 1...
[2021-10-29 17:10:56] Bias-correcting 1 members separately...
[2021-10-29 17:10:57] Done.
Validation 15, 7 remaining
[2021-10-29 17:10:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:58] Number of windows considered: 1...
[2021-10-29 17:10:58] Bias-correcting 1 members separately...
[2021-10-29 17:10:58] Done.
Validation 16, 6 remaining
[2021-10-29 17:10:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:10:59] Number of windows considered: 1...
[2021-10-29 17:10:59] Bias-correcting 1 members separately...
[2021-10-29 17:10:59] Done.
Validation 17, 5 remaining
[2021-10-29 17:11:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:00] Number of windows considered: 1...
[2021-10-29 17:11:00] Bias-correcting 1 members separately...
[2021-10-29 17:11:00] Done.
Validation 18, 4 remaining
[2021-10-29 17:11:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:01] Number of windows considered: 1...
[2021-10-29 17:11:01] Bias-correcting 1 members separately...
[2021-10-29 17:11:01] Done.
Validation 19, 3 remaining
[2021-10-29 17:11:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:02] Number of windows considered: 1...
[2021-10-29 17:11:02] Bias-correcting 1 members separately...
[2021-10-29 17:11:02] Done.
Validation 20, 2 remaining
[2021-10-29 17:11:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:03] Number of windows considered: 1...
[2021-10-29 17:11:03] Bias-correcting 1 members separately...
[2021-10-29 17:11:03] Done.
Validation 21, 1 remaining
[2021-10-29 17:11:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:04] Number of windows considered: 1...
[2021-10-29 17:11:04] Bias-correcting 1 members separately...
[2021-10-29 17:11:04] Done.
Validation 22, 0 remaining
[2021-10-29 17:11:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:05] Number of windows considered: 1...
[2021-10-29 17:11:05] Bias-correcting 1 members separately...
[2021-10-29 17:11:05] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:11:06] Performing annual aggregation...
[2021-10-29 17:11:06] Done.
[2021-10-29 17:11:06] - Computing climatology...
[2021-10-29 17:11:06] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.eqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", cross.val = "loo")
Validation 1, 21 remaining
[2021-10-29 17:11:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:07] Number of windows considered: 1...
[2021-10-29 17:11:07] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:07] Done.
Validation 2, 20 remaining
[2021-10-29 17:11:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:08] Number of windows considered: 1...
[2021-10-29 17:11:08] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:09] Done.
Validation 3, 19 remaining
[2021-10-29 17:11:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:10] Number of windows considered: 1...
[2021-10-29 17:11:10] Bias-correcting 1 members separately...
[2021-10-29 17:11:10] Done.
Validation 4, 18 remaining
[2021-10-29 17:11:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:11] Number of windows considered: 1...
[2021-10-29 17:11:11] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:11] Done.
Validation 5, 17 remaining
[2021-10-29 17:11:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:12] Number of windows considered: 1...
[2021-10-29 17:11:12] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:12] Done.
Validation 6, 16 remaining
[2021-10-29 17:11:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:13] Number of windows considered: 1...
[2021-10-29 17:11:13] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:13] Done.
Validation 7, 15 remaining
[2021-10-29 17:11:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:14] Number of windows considered: 1...
[2021-10-29 17:11:14] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:15] Done.
Validation 8, 14 remaining
[2021-10-29 17:11:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:16] Number of windows considered: 1...
[2021-10-29 17:11:16] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:16] Done.
Validation 9, 13 remaining
[2021-10-29 17:11:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:17] Number of windows considered: 1...
[2021-10-29 17:11:17] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:17] Done.
Validation 10, 12 remaining
[2021-10-29 17:11:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:18] Number of windows considered: 1...
[2021-10-29 17:11:18] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:19] Done.
Validation 11, 11 remaining
[2021-10-29 17:11:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:20] Number of windows considered: 1...
[2021-10-29 17:11:20] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:20] Done.
Validation 12, 10 remaining
[2021-10-29 17:11:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:21] Number of windows considered: 1...
[2021-10-29 17:11:21] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:21] Done.
Validation 13, 9 remaining
[2021-10-29 17:11:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:22] Number of windows considered: 1...
[2021-10-29 17:11:22] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:22] Done.
Validation 14, 8 remaining
[2021-10-29 17:11:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:23] Number of windows considered: 1...
[2021-10-29 17:11:23] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:24] Done.
Validation 15, 7 remaining
[2021-10-29 17:11:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:25] Number of windows considered: 1...
[2021-10-29 17:11:25] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:25] Done.
Validation 16, 6 remaining
[2021-10-29 17:11:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:26] Number of windows considered: 1...
[2021-10-29 17:11:26] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:26] Done.
Validation 17, 5 remaining
[2021-10-29 17:11:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:27] Number of windows considered: 1...
[2021-10-29 17:11:27] Bias-correcting 1 members separately...
[2021-10-29 17:11:28] Done.
Validation 18, 4 remaining
[2021-10-29 17:11:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:29] Number of windows considered: 1...
[2021-10-29 17:11:29] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:29] Done.
Validation 19, 3 remaining
[2021-10-29 17:11:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:30] Number of windows considered: 1...
[2021-10-29 17:11:30] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:30] Done.
Validation 20, 2 remaining
[2021-10-29 17:11:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:31] Number of windows considered: 1...
[2021-10-29 17:11:31] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:31] Done.
Validation 21, 1 remaining
[2021-10-29 17:11:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:32] Number of windows considered: 1...
[2021-10-29 17:11:32] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:33] Done.
Validation 22, 0 remaining
[2021-10-29 17:11:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:34] Number of windows considered: 1...
[2021-10-29 17:11:34] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:11:34] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:11:35] Performing annual aggregation...
[2021-10-29 17:11:35] Done.
[2021-10-29 17:11:35] - Computing climatology...
[2021-10-29 17:11:35] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", theta = .7, cross.val = "loo")
Validation 1, 21 remaining
[2021-10-29 17:11:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:36] Number of windows considered: 1...
[2021-10-29 17:11:36] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:36] Done.
Validation 2, 20 remaining
[2021-10-29 17:11:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:37] Number of windows considered: 1...
[2021-10-29 17:11:37] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:37] Done.
Validation 3, 19 remaining
[2021-10-29 17:11:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:39] Number of windows considered: 1...
[2021-10-29 17:11:39] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:39] Done.
Validation 4, 18 remaining
[2021-10-29 17:11:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:40] Number of windows considered: 1...
[2021-10-29 17:11:40] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:40] Done.
Validation 5, 17 remaining
[2021-10-29 17:11:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:41] Number of windows considered: 1...
[2021-10-29 17:11:41] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:41] Done.
Validation 6, 16 remaining
[2021-10-29 17:11:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:42] Number of windows considered: 1...
[2021-10-29 17:11:42] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:43] Done.
Validation 7, 15 remaining
[2021-10-29 17:11:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:44] Number of windows considered: 1...
[2021-10-29 17:11:44] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:44] Done.
Validation 8, 14 remaining
[2021-10-29 17:11:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:45] Number of windows considered: 1...
[2021-10-29 17:11:45] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:45] Done.
Validation 9, 13 remaining
[2021-10-29 17:11:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:46] Number of windows considered: 1...
[2021-10-29 17:11:46] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:46] Done.
Validation 10, 12 remaining
[2021-10-29 17:11:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:47] Number of windows considered: 1...
[2021-10-29 17:11:47] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:47] Done.
Validation 11, 11 remaining
[2021-10-29 17:11:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:48] Number of windows considered: 1...
[2021-10-29 17:11:49] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:49] Done.
Validation 12, 10 remaining
[2021-10-29 17:11:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:50] Number of windows considered: 1...
[2021-10-29 17:11:50] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:50] Done.
Validation 13, 9 remaining
[2021-10-29 17:11:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:51] Number of windows considered: 1...
[2021-10-29 17:11:51] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:51] Done.
Validation 14, 8 remaining
[2021-10-29 17:11:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:52] Number of windows considered: 1...
[2021-10-29 17:11:52] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:52] Done.
Validation 15, 7 remaining
[2021-10-29 17:11:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:53] Number of windows considered: 1...
[2021-10-29 17:11:53] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:54] Done.
Validation 16, 6 remaining
[2021-10-29 17:11:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:55] Number of windows considered: 1...
[2021-10-29 17:11:55] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:55] Done.
Validation 17, 5 remaining
[2021-10-29 17:11:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:56] Number of windows considered: 1...
[2021-10-29 17:11:56] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:56] Done.
Validation 18, 4 remaining
[2021-10-29 17:11:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:57] Number of windows considered: 1...
[2021-10-29 17:11:57] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:57] Done.
Validation 19, 3 remaining
[2021-10-29 17:11:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:11:59] Number of windows considered: 1...
[2021-10-29 17:11:59] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:11:59] Done.
Validation 20, 2 remaining
[2021-10-29 17:12:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:00] Number of windows considered: 1...
[2021-10-29 17:12:00] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:12:00] Done.
Validation 21, 1 remaining
[2021-10-29 17:12:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:01] Number of windows considered: 1...
[2021-10-29 17:12:01] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:12:01] Done.
Validation 22, 0 remaining
[2021-10-29 17:12:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:02] Number of windows considered: 1...
[2021-10-29 17:12:02] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:12:03] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:12:03] Performing annual aggregation...
[2021-10-29 17:12:03] Done.
[2021-10-29 17:12:03] - Computing climatology...
[2021-10-29 17:12:03] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm2.complete <- index.cal.station.complete
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.trmm.complete[i]-index.obs.complete[i]),abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
score.trmm <- c()
for (i in c(1:9)) {
score.trmm <- c(score.trmm, norm.vector[[i]][1])
}
score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][2])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][3])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][4])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][5])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
EQM-C PQM-C GPQM2-C GPQM-C TRMM
0.9453403 0.8435521 0.5441631 0.4500923 0.3928099
scores.complete <- scores
paste(names(scores.st4.wt1[1]),names(scores.st4.wt2[1]),names(scores.st4.wt3[1]),names(scores.st4.wt4[1]),names(scores.st4.wt5[1]), names(scores.complete[1]))
[1] "EQM-WT1 EQM-WT2 PQM-WT3 EQM-WT4 EQM-WT5 EQM-C"
Combination of techniques by WT
cal.station.cl1.eqm <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "eqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 17:12:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:05] Number of windows considered: 1...
[2021-10-29 17:12:05] Bias-correcting 1 members separately...
[2021-10-29 17:12:05] Done.
Validation 2, 20 remaining
[2021-10-29 17:12:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:06] Number of windows considered: 1...
[2021-10-29 17:12:06] Bias-correcting 1 members separately...
[2021-10-29 17:12:06] Done.
Validation 3, 19 remaining
[2021-10-29 17:12:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:07] Number of windows considered: 1...
[2021-10-29 17:12:07] Bias-correcting 1 members separately...
[2021-10-29 17:12:07] Done.
Validation 4, 18 remaining
[2021-10-29 17:12:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:08] Number of windows considered: 1...
[2021-10-29 17:12:08] Bias-correcting 1 members separately...
[2021-10-29 17:12:09] Done.
Validation 5, 17 remaining
[2021-10-29 17:12:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:10] Number of windows considered: 1...
[2021-10-29 17:12:10] Bias-correcting 1 members separately...
[2021-10-29 17:12:10] Done.
Validation 6, 16 remaining
[2021-10-29 17:12:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:11] Number of windows considered: 1...
[2021-10-29 17:12:11] Bias-correcting 1 members separately...
[2021-10-29 17:12:11] Done.
Validation 7, 15 remaining
[2021-10-29 17:12:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:12] Number of windows considered: 1...
[2021-10-29 17:12:12] Bias-correcting 1 members separately...
[2021-10-29 17:12:12] Done.
Validation 8, 14 remaining
[2021-10-29 17:12:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:14] Number of windows considered: 1...
[2021-10-29 17:12:14] Bias-correcting 1 members separately...
[2021-10-29 17:12:14] Done.
Validation 9, 13 remaining
[2021-10-29 17:12:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:15] Number of windows considered: 1...
[2021-10-29 17:12:15] Bias-correcting 1 members separately...
[2021-10-29 17:12:15] Done.
Validation 10, 12 remaining
[2021-10-29 17:12:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:16] Number of windows considered: 1...
[2021-10-29 17:12:16] Bias-correcting 1 members separately...
[2021-10-29 17:12:16] Done.
Validation 11, 11 remaining
[2021-10-29 17:12:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:17] Number of windows considered: 1...
[2021-10-29 17:12:17] Bias-correcting 1 members separately...
[2021-10-29 17:12:17] Done.
Validation 12, 10 remaining
[2021-10-29 17:12:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:19] Number of windows considered: 1...
[2021-10-29 17:12:19] Bias-correcting 1 members separately...
[2021-10-29 17:12:19] Done.
Validation 13, 9 remaining
[2021-10-29 17:12:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:20] Number of windows considered: 1...
[2021-10-29 17:12:20] Bias-correcting 1 members separately...
[2021-10-29 17:12:20] Done.
Validation 14, 8 remaining
[2021-10-29 17:12:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:21] Number of windows considered: 1...
[2021-10-29 17:12:21] Bias-correcting 1 members separately...
[2021-10-29 17:12:21] Done.
Validation 15, 7 remaining
[2021-10-29 17:12:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:23] Number of windows considered: 1...
[2021-10-29 17:12:23] Bias-correcting 1 members separately...
[2021-10-29 17:12:23] Done.
Validation 16, 6 remaining
[2021-10-29 17:12:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:24] Number of windows considered: 1...
[2021-10-29 17:12:24] Bias-correcting 1 members separately...
[2021-10-29 17:12:24] Done.
Validation 17, 5 remaining
[2021-10-29 17:12:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:25] Number of windows considered: 1...
[2021-10-29 17:12:25] Bias-correcting 1 members separately...
[2021-10-29 17:12:25] Done.
Validation 18, 4 remaining
[2021-10-29 17:12:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:26] Number of windows considered: 1...
[2021-10-29 17:12:26] Bias-correcting 1 members separately...
[2021-10-29 17:12:27] Done.
Validation 19, 3 remaining
[2021-10-29 17:12:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:28] Number of windows considered: 1...
[2021-10-29 17:12:28] Bias-correcting 1 members separately...
[2021-10-29 17:12:28] Done.
Validation 20, 2 remaining
[2021-10-29 17:12:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:29] Number of windows considered: 1...
[2021-10-29 17:12:29] Bias-correcting 1 members separately...
[2021-10-29 17:12:29] Done.
Validation 21, 1 remaining
[2021-10-29 17:12:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:30] Number of windows considered: 1...
[2021-10-29 17:12:30] Bias-correcting 1 members separately...
[2021-10-29 17:12:31] Done.
Validation 22, 0 remaining
[2021-10-29 17:12:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:32] Number of windows considered: 1...
[2021-10-29 17:12:32] Bias-correcting 1 members separately...
[2021-10-29 17:12:32] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl1.eqm$Dates$start <- as.POSIXct(cal.station.cl1.eqm$Dates$start,tz = "GMT")
cal.station.cl1.eqm$Dates$end <- as.POSIXct(cal.station.cl1.eqm$Dates$end,tz = "GMT")
cal.station.cl2.eqm <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "eqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 17:12:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:34] Number of windows considered: 1...
[2021-10-29 17:12:34] Bias-correcting 1 members separately...
[2021-10-29 17:12:34] Done.
Validation 2, 20 remaining
[2021-10-29 17:12:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:35] Number of windows considered: 1...
[2021-10-29 17:12:35] Bias-correcting 1 members separately...
[2021-10-29 17:12:35] Done.
Validation 3, 19 remaining
[2021-10-29 17:12:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:36] Number of windows considered: 1...
[2021-10-29 17:12:36] Bias-correcting 1 members separately...
[2021-10-29 17:12:36] Done.
Validation 4, 18 remaining
[2021-10-29 17:12:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:38] Number of windows considered: 1...
[2021-10-29 17:12:38] Bias-correcting 1 members separately...
[2021-10-29 17:12:38] Done.
Validation 5, 17 remaining
[2021-10-29 17:12:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:39] Number of windows considered: 1...
[2021-10-29 17:12:39] Bias-correcting 1 members separately...
[2021-10-29 17:12:39] Done.
Validation 6, 16 remaining
[2021-10-29 17:12:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:40] Number of windows considered: 1...
[2021-10-29 17:12:40] Bias-correcting 1 members separately...
[2021-10-29 17:12:40] Done.
Validation 7, 15 remaining
[2021-10-29 17:12:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:41] Number of windows considered: 1...
[2021-10-29 17:12:41] Bias-correcting 1 members separately...
[2021-10-29 17:12:42] Done.
Validation 8, 14 remaining
[2021-10-29 17:12:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:43] Number of windows considered: 1...
[2021-10-29 17:12:43] Bias-correcting 1 members separately...
[2021-10-29 17:12:43] Done.
Validation 9, 13 remaining
[2021-10-29 17:12:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:44] Number of windows considered: 1...
[2021-10-29 17:12:44] Bias-correcting 1 members separately...
[2021-10-29 17:12:44] Done.
Validation 10, 12 remaining
[2021-10-29 17:12:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:46] Number of windows considered: 1...
[2021-10-29 17:12:46] Bias-correcting 1 members separately...
[2021-10-29 17:12:46] Done.
Validation 11, 11 remaining
[2021-10-29 17:12:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:47] Number of windows considered: 1...
[2021-10-29 17:12:47] Bias-correcting 1 members separately...
[2021-10-29 17:12:47] Done.
Validation 12, 10 remaining
[2021-10-29 17:12:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:48] Number of windows considered: 1...
[2021-10-29 17:12:48] Bias-correcting 1 members separately...
[2021-10-29 17:12:48] Done.
Validation 13, 9 remaining
[2021-10-29 17:12:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:49] Number of windows considered: 1...
[2021-10-29 17:12:49] Bias-correcting 1 members separately...
[2021-10-29 17:12:49] Done.
Validation 14, 8 remaining
[2021-10-29 17:12:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:50] Number of windows considered: 1...
[2021-10-29 17:12:50] Bias-correcting 1 members separately...
[2021-10-29 17:12:50] Done.
Validation 15, 7 remaining
[2021-10-29 17:12:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:51] Number of windows considered: 1...
[2021-10-29 17:12:51] Bias-correcting 1 members separately...
[2021-10-29 17:12:51] Done.
Validation 16, 6 remaining
[2021-10-29 17:12:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:52] Number of windows considered: 1...
[2021-10-29 17:12:52] Bias-correcting 1 members separately...
[2021-10-29 17:12:52] Done.
Validation 17, 5 remaining
[2021-10-29 17:12:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:53] Number of windows considered: 1...
[2021-10-29 17:12:53] Bias-correcting 1 members separately...
[2021-10-29 17:12:53] Done.
Validation 18, 4 remaining
[2021-10-29 17:12:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:54] Number of windows considered: 1...
[2021-10-29 17:12:54] Bias-correcting 1 members separately...
[2021-10-29 17:12:54] Done.
Validation 19, 3 remaining
[2021-10-29 17:12:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:55] Number of windows considered: 1...
[2021-10-29 17:12:55] Bias-correcting 1 members separately...
[2021-10-29 17:12:55] Done.
Validation 20, 2 remaining
[2021-10-29 17:12:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:56] Number of windows considered: 1...
[2021-10-29 17:12:56] Bias-correcting 1 members separately...
[2021-10-29 17:12:56] Done.
Validation 21, 1 remaining
[2021-10-29 17:12:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:57] Number of windows considered: 1...
[2021-10-29 17:12:57] Bias-correcting 1 members separately...
[2021-10-29 17:12:57] Done.
Validation 22, 0 remaining
[2021-10-29 17:12:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:12:58] Number of windows considered: 1...
[2021-10-29 17:12:58] Bias-correcting 1 members separately...
[2021-10-29 17:12:58] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl2.eqm$Dates$start <- as.POSIXct(cal.station.cl2.eqm$Dates$start,tz = "GMT")
cal.station.cl2.eqm$Dates$end <- as.POSIXct(cal.station.cl2.eqm$Dates$end,tz = "GMT")
cal.station.cl3.pqm <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "pqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 17:13:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:00] Number of windows considered: 1...
[2021-10-29 17:13:00] Bias-correcting 1 members separately...
[2021-10-29 17:13:00] Done.
Validation 2, 20 remaining
[2021-10-29 17:13:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:01] Number of windows considered: 1...
[2021-10-29 17:13:01] Bias-correcting 1 members separately...
[2021-10-29 17:13:01] Done.
Validation 3, 19 remaining
[2021-10-29 17:13:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:02] Number of windows considered: 1...
[2021-10-29 17:13:02] Bias-correcting 1 members separately...
[2021-10-29 17:13:02] Done.
Validation 4, 18 remaining
[2021-10-29 17:13:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:03] Number of windows considered: 1...
[2021-10-29 17:13:03] Bias-correcting 1 members separately...
[2021-10-29 17:13:03] Done.
Validation 5, 17 remaining
[2021-10-29 17:13:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:04] Number of windows considered: 1...
[2021-10-29 17:13:04] Bias-correcting 1 members separately...
[2021-10-29 17:13:04] Done.
Validation 6, 16 remaining
[2021-10-29 17:13:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:05] Number of windows considered: 1...
[2021-10-29 17:13:05] Bias-correcting 1 members separately...
[2021-10-29 17:13:05] Done.
Validation 7, 15 remaining
[2021-10-29 17:13:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:06] Number of windows considered: 1...
[2021-10-29 17:13:06] Bias-correcting 1 members separately...
[2021-10-29 17:13:06] Done.
Validation 8, 14 remaining
[2021-10-29 17:13:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:07] Number of windows considered: 1...
[2021-10-29 17:13:07] Bias-correcting 1 members separately...
[2021-10-29 17:13:07] Done.
Validation 9, 13 remaining
[2021-10-29 17:13:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:08] Number of windows considered: 1...
[2021-10-29 17:13:08] Bias-correcting 1 members separately...
[2021-10-29 17:13:08] Done.
Validation 10, 12 remaining
[2021-10-29 17:13:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:09] Number of windows considered: 1...
[2021-10-29 17:13:09] Bias-correcting 1 members separately...
[2021-10-29 17:13:09] Done.
Validation 11, 11 remaining
[2021-10-29 17:13:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:10] Number of windows considered: 1...
[2021-10-29 17:13:10] Bias-correcting 1 members separately...
[2021-10-29 17:13:10] Done.
Validation 12, 10 remaining
[2021-10-29 17:13:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:11] Number of windows considered: 1...
[2021-10-29 17:13:11] Bias-correcting 1 members separately...
[2021-10-29 17:13:11] Done.
Validation 13, 9 remaining
[2021-10-29 17:13:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:12] Number of windows considered: 1...
[2021-10-29 17:13:12] Bias-correcting 1 members separately...
[2021-10-29 17:13:12] Done.
Validation 14, 8 remaining
[2021-10-29 17:13:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:13] Number of windows considered: 1...
[2021-10-29 17:13:13] Bias-correcting 1 members separately...
[2021-10-29 17:13:13] Done.
Validation 15, 7 remaining
[2021-10-29 17:13:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:14] Number of windows considered: 1...
[2021-10-29 17:13:14] Bias-correcting 1 members separately...
[2021-10-29 17:13:14] Done.
Validation 16, 6 remaining
[2021-10-29 17:13:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:16] Number of windows considered: 1...
[2021-10-29 17:13:16] Bias-correcting 1 members separately...
[2021-10-29 17:13:16] Done.
Validation 17, 5 remaining
[2021-10-29 17:13:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:17] Number of windows considered: 1...
[2021-10-29 17:13:17] Bias-correcting 1 members separately...
[2021-10-29 17:13:17] Done.
Validation 18, 4 remaining
[2021-10-29 17:13:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:18] Number of windows considered: 1...
[2021-10-29 17:13:18] Bias-correcting 1 members separately...
[2021-10-29 17:13:18] Done.
Validation 19, 3 remaining
[2021-10-29 17:13:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:19] Number of windows considered: 1...
[2021-10-29 17:13:19] Bias-correcting 1 members separately...
[2021-10-29 17:13:19] Done.
Validation 20, 2 remaining
[2021-10-29 17:13:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:20] Number of windows considered: 1...
[2021-10-29 17:13:20] Bias-correcting 1 members separately...
[2021-10-29 17:13:20] Done.
Validation 21, 1 remaining
[2021-10-29 17:13:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:21] Number of windows considered: 1...
[2021-10-29 17:13:21] Bias-correcting 1 members separately...
[2021-10-29 17:13:21] Done.
Validation 22, 0 remaining
[2021-10-29 17:13:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:22] Number of windows considered: 1...
[2021-10-29 17:13:22] Bias-correcting 1 members separately...
[2021-10-29 17:13:22] Done.
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl3.pqm$Dates$start <- as.POSIXct(cal.station.cl3.pqm$Dates$start,tz = "GMT")
cal.station.cl3.pqm$Dates$end <- as.POSIXct(cal.station.cl3.pqm$Dates$end,tz = "GMT")
cal.station.cl4.eqm <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "eqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 17:13:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:23] Number of windows considered: 1...
[2021-10-29 17:13:23] Bias-correcting 1 members separately...
[2021-10-29 17:13:24] Done.
Validation 2, 20 remaining
[2021-10-29 17:13:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:25] Number of windows considered: 1...
[2021-10-29 17:13:25] Bias-correcting 1 members separately...
[2021-10-29 17:13:25] Done.
Validation 3, 19 remaining
[2021-10-29 17:13:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:26] Number of windows considered: 1...
[2021-10-29 17:13:26] Bias-correcting 1 members separately...
[2021-10-29 17:13:26] Done.
Validation 4, 18 remaining
[2021-10-29 17:13:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:27] Number of windows considered: 1...
[2021-10-29 17:13:27] Bias-correcting 1 members separately...
[2021-10-29 17:13:27] Done.
Validation 5, 17 remaining
[2021-10-29 17:13:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:28] Number of windows considered: 1...
[2021-10-29 17:13:28] Bias-correcting 1 members separately...
[2021-10-29 17:13:28] Done.
Validation 6, 16 remaining
[2021-10-29 17:13:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:30] Number of windows considered: 1...
[2021-10-29 17:13:30] Bias-correcting 1 members separately...
[2021-10-29 17:13:30] Done.
Validation 7, 15 remaining
[2021-10-29 17:13:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:31] Number of windows considered: 1...
[2021-10-29 17:13:31] Bias-correcting 1 members separately...
[2021-10-29 17:13:31] Done.
Validation 8, 14 remaining
[2021-10-29 17:13:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:32] Number of windows considered: 1...
[2021-10-29 17:13:32] Bias-correcting 1 members separately...
[2021-10-29 17:13:32] Done.
Validation 9, 13 remaining
[2021-10-29 17:13:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:33] Number of windows considered: 1...
[2021-10-29 17:13:33] Bias-correcting 1 members separately...
[2021-10-29 17:13:34] Done.
Validation 10, 12 remaining
[2021-10-29 17:13:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:35] Number of windows considered: 1...
[2021-10-29 17:13:35] Bias-correcting 1 members separately...
[2021-10-29 17:13:35] Done.
Validation 11, 11 remaining
[2021-10-29 17:13:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:36] Number of windows considered: 1...
[2021-10-29 17:13:36] Bias-correcting 1 members separately...
[2021-10-29 17:13:36] Done.
Validation 12, 10 remaining
[2021-10-29 17:13:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:37] Number of windows considered: 1...
[2021-10-29 17:13:37] Bias-correcting 1 members separately...
[2021-10-29 17:13:37] Done.
Validation 13, 9 remaining
[2021-10-29 17:13:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:38] Number of windows considered: 1...
[2021-10-29 17:13:38] Bias-correcting 1 members separately...
[2021-10-29 17:13:39] Done.
Validation 14, 8 remaining
[2021-10-29 17:13:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:40] Number of windows considered: 1...
[2021-10-29 17:13:40] Bias-correcting 1 members separately...
[2021-10-29 17:13:40] Done.
Validation 15, 7 remaining
[2021-10-29 17:13:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:41] Number of windows considered: 1...
[2021-10-29 17:13:41] Bias-correcting 1 members separately...
[2021-10-29 17:13:41] Done.
Validation 16, 6 remaining
[2021-10-29 17:13:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:42] Number of windows considered: 1...
[2021-10-29 17:13:42] Bias-correcting 1 members separately...
[2021-10-29 17:13:42] Done.
Validation 17, 5 remaining
[2021-10-29 17:13:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:43] Number of windows considered: 1...
[2021-10-29 17:13:43] Bias-correcting 1 members separately...
[2021-10-29 17:13:43] Done.
Validation 18, 4 remaining
[2021-10-29 17:13:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:45] Number of windows considered: 1...
[2021-10-29 17:13:45] Bias-correcting 1 members separately...
[2021-10-29 17:13:45] Done.
Validation 19, 3 remaining
[2021-10-29 17:13:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:46] Number of windows considered: 1...
[2021-10-29 17:13:46] Bias-correcting 1 members separately...
[2021-10-29 17:13:46] Done.
Validation 20, 2 remaining
[2021-10-29 17:13:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:47] Number of windows considered: 1...
[2021-10-29 17:13:47] Bias-correcting 1 members separately...
[2021-10-29 17:13:47] Done.
Validation 21, 1 remaining
[2021-10-29 17:13:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:48] Number of windows considered: 1...
[2021-10-29 17:13:48] Bias-correcting 1 members separately...
[2021-10-29 17:13:48] Done.
Validation 22, 0 remaining
[2021-10-29 17:13:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:50] Number of windows considered: 1...
[2021-10-29 17:13:50] Bias-correcting 1 members separately...
[2021-10-29 17:13:50] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl4.eqm$Dates$start <- as.POSIXct(cal.station.cl4.eqm$Dates$start,tz = "GMT")
cal.station.cl4.eqm$Dates$end <- as.POSIXct(cal.station.cl4.eqm$Dates$end,tz = "GMT")
cal.station.cl5.eqm <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "eqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 17:13:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:52] Number of windows considered: 1...
[2021-10-29 17:13:52] Bias-correcting 1 members separately...
[2021-10-29 17:13:52] Done.
Validation 2, 20 remaining
[2021-10-29 17:13:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:53] Number of windows considered: 1...
[2021-10-29 17:13:53] Bias-correcting 1 members separately...
[2021-10-29 17:13:53] Done.
Validation 3, 19 remaining
[2021-10-29 17:13:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:54] Number of windows considered: 1...
[2021-10-29 17:13:54] Bias-correcting 1 members separately...
[2021-10-29 17:13:54] Done.
Validation 4, 18 remaining
[2021-10-29 17:13:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:56] Number of windows considered: 1...
[2021-10-29 17:13:56] Bias-correcting 1 members separately...
[2021-10-29 17:13:56] Done.
Validation 5, 17 remaining
[2021-10-29 17:13:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:57] Number of windows considered: 1...
[2021-10-29 17:13:57] Bias-correcting 1 members separately...
[2021-10-29 17:13:57] Done.
Validation 6, 16 remaining
[2021-10-29 17:13:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:58] Number of windows considered: 1...
[2021-10-29 17:13:58] Bias-correcting 1 members separately...
[2021-10-29 17:13:58] Done.
Validation 7, 15 remaining
[2021-10-29 17:13:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:13:59] Number of windows considered: 1...
[2021-10-29 17:13:59] Bias-correcting 1 members separately...
[2021-10-29 17:14:00] Done.
Validation 8, 14 remaining
[2021-10-29 17:14:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:01] Number of windows considered: 1...
[2021-10-29 17:14:01] Bias-correcting 1 members separately...
[2021-10-29 17:14:01] Done.
Validation 9, 13 remaining
[2021-10-29 17:14:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:02] Number of windows considered: 1...
[2021-10-29 17:14:02] Bias-correcting 1 members separately...
[2021-10-29 17:14:02] Done.
Validation 10, 12 remaining
[2021-10-29 17:14:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:03] Number of windows considered: 1...
[2021-10-29 17:14:03] Bias-correcting 1 members separately...
[2021-10-29 17:14:04] Done.
Validation 11, 11 remaining
[2021-10-29 17:14:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:05] Number of windows considered: 1...
[2021-10-29 17:14:05] Bias-correcting 1 members separately...
[2021-10-29 17:14:05] Done.
Validation 12, 10 remaining
[2021-10-29 17:14:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:06] Number of windows considered: 1...
[2021-10-29 17:14:06] Bias-correcting 1 members separately...
[2021-10-29 17:14:06] Done.
Validation 13, 9 remaining
[2021-10-29 17:14:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:08] Number of windows considered: 1...
[2021-10-29 17:14:08] Bias-correcting 1 members separately...
[2021-10-29 17:14:08] Done.
Validation 14, 8 remaining
[2021-10-29 17:14:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:09] Number of windows considered: 1...
[2021-10-29 17:14:09] Bias-correcting 1 members separately...
[2021-10-29 17:14:09] Done.
Validation 15, 7 remaining
[2021-10-29 17:14:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:10] Number of windows considered: 1...
[2021-10-29 17:14:10] Bias-correcting 1 members separately...
[2021-10-29 17:14:10] Done.
Validation 16, 6 remaining
[2021-10-29 17:14:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:11] Number of windows considered: 1...
[2021-10-29 17:14:11] Bias-correcting 1 members separately...
[2021-10-29 17:14:12] Done.
Validation 17, 5 remaining
[2021-10-29 17:14:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:13] Number of windows considered: 1...
[2021-10-29 17:14:13] Bias-correcting 1 members separately...
[2021-10-29 17:14:13] Done.
Validation 18, 4 remaining
[2021-10-29 17:14:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:14] Number of windows considered: 1...
[2021-10-29 17:14:14] Bias-correcting 1 members separately...
[2021-10-29 17:14:14] Done.
Validation 19, 3 remaining
[2021-10-29 17:14:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:15] Number of windows considered: 1...
[2021-10-29 17:14:15] Bias-correcting 1 members separately...
[2021-10-29 17:14:16] Done.
Validation 20, 2 remaining
[2021-10-29 17:14:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:17] Number of windows considered: 1...
[2021-10-29 17:14:17] Bias-correcting 1 members separately...
[2021-10-29 17:14:17] Done.
Validation 21, 1 remaining
[2021-10-29 17:14:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:18] Number of windows considered: 1...
[2021-10-29 17:14:18] Bias-correcting 1 members separately...
[2021-10-29 17:14:18] Done.
Validation 22, 0 remaining
[2021-10-29 17:14:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:19] Number of windows considered: 1...
[2021-10-29 17:14:19] Bias-correcting 1 members separately...
[2021-10-29 17:14:20] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl5.eqm$Dates$start <- as.POSIXct(cal.station.cl5.eqm$Dates$start,tz = "GMT")
cal.station.cl5.eqm$Dates$end <- as.POSIXct(cal.station.cl5.eqm$Dates$end,tz = "GMT")
idx <- which(!is.na(cal.station.cl1.eqm$Data))
cal.station.cl1.eqm <- subsetDimension(cal.station.cl1.eqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl2.eqm$Data))
cal.station.cl2.eqm <- subsetDimension(cal.station.cl2.eqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl3.pqm$Data))
cal.station.cl3.pqm <- subsetDimension(cal.station.cl3.pqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl4.eqm$Data))
cal.station.cl4.eqm <- subsetDimension(cal.station.cl4.eqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl5.eqm$Data))
cal.station.cl5.eqm <- subsetDimension(cal.station.cl5.eqm, dimension = "time", indices = idx)
wt_conditioned <- bindGrid(cal.station.cl1.eqm, cal.station.cl2.eqm, cal.station.cl3.pqm,
cal.station.cl4.eqm, cal.station.cl5.eqm, dimension = "time")
attr(wt_conditioned$Data, "dimensions") <- "time"
#cambiar de tipo de biasCorrection y fillGridDates
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "eqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-10-29 17:14:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:22] Number of windows considered: 1...
[2021-10-29 17:14:22] Bias-correcting 1 members separately...
[2021-10-29 17:14:22] Done.
Validation 2, 20 remaining
[2021-10-29 17:14:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:24] Number of windows considered: 1...
[2021-10-29 17:14:24] Bias-correcting 1 members separately...
[2021-10-29 17:14:24] Done.
Validation 3, 19 remaining
[2021-10-29 17:14:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:25] Number of windows considered: 1...
[2021-10-29 17:14:25] Bias-correcting 1 members separately...
[2021-10-29 17:14:25] Done.
Validation 4, 18 remaining
[2021-10-29 17:14:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:26] Number of windows considered: 1...
[2021-10-29 17:14:26] Bias-correcting 1 members separately...
[2021-10-29 17:14:26] Done.
Validation 5, 17 remaining
[2021-10-29 17:14:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:27] Number of windows considered: 1...
[2021-10-29 17:14:27] Bias-correcting 1 members separately...
[2021-10-29 17:14:27] Done.
Validation 6, 16 remaining
[2021-10-29 17:14:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:28] Number of windows considered: 1...
[2021-10-29 17:14:28] Bias-correcting 1 members separately...
[2021-10-29 17:14:28] Done.
Validation 7, 15 remaining
[2021-10-29 17:14:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:29] Number of windows considered: 1...
[2021-10-29 17:14:29] Bias-correcting 1 members separately...
[2021-10-29 17:14:29] Done.
Validation 8, 14 remaining
[2021-10-29 17:14:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:30] Number of windows considered: 1...
[2021-10-29 17:14:30] Bias-correcting 1 members separately...
[2021-10-29 17:14:30] Done.
Validation 9, 13 remaining
[2021-10-29 17:14:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:31] Number of windows considered: 1...
[2021-10-29 17:14:31] Bias-correcting 1 members separately...
[2021-10-29 17:14:31] Done.
Validation 10, 12 remaining
[2021-10-29 17:14:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:32] Number of windows considered: 1...
[2021-10-29 17:14:32] Bias-correcting 1 members separately...
[2021-10-29 17:14:32] Done.
Validation 11, 11 remaining
[2021-10-29 17:14:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:33] Number of windows considered: 1...
[2021-10-29 17:14:33] Bias-correcting 1 members separately...
[2021-10-29 17:14:33] Done.
Validation 12, 10 remaining
[2021-10-29 17:14:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:34] Number of windows considered: 1...
[2021-10-29 17:14:34] Bias-correcting 1 members separately...
[2021-10-29 17:14:34] Done.
Validation 13, 9 remaining
[2021-10-29 17:14:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:35] Number of windows considered: 1...
[2021-10-29 17:14:35] Bias-correcting 1 members separately...
[2021-10-29 17:14:35] Done.
Validation 14, 8 remaining
[2021-10-29 17:14:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:36] Number of windows considered: 1...
[2021-10-29 17:14:36] Bias-correcting 1 members separately...
[2021-10-29 17:14:36] Done.
Validation 15, 7 remaining
[2021-10-29 17:14:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:37] Number of windows considered: 1...
[2021-10-29 17:14:37] Bias-correcting 1 members separately...
[2021-10-29 17:14:37] Done.
Validation 16, 6 remaining
[2021-10-29 17:14:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:38] Number of windows considered: 1...
[2021-10-29 17:14:38] Bias-correcting 1 members separately...
[2021-10-29 17:14:38] Done.
Validation 17, 5 remaining
[2021-10-29 17:14:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:39] Number of windows considered: 1...
[2021-10-29 17:14:39] Bias-correcting 1 members separately...
[2021-10-29 17:14:39] Done.
Validation 18, 4 remaining
[2021-10-29 17:14:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:40] Number of windows considered: 1...
[2021-10-29 17:14:40] Bias-correcting 1 members separately...
[2021-10-29 17:14:41] Done.
Validation 19, 3 remaining
[2021-10-29 17:14:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:42] Number of windows considered: 1...
[2021-10-29 17:14:42] Bias-correcting 1 members separately...
[2021-10-29 17:14:42] Done.
Validation 20, 2 remaining
[2021-10-29 17:14:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:43] Number of windows considered: 1...
[2021-10-29 17:14:43] Bias-correcting 1 members separately...
[2021-10-29 17:14:43] Done.
Validation 21, 1 remaining
[2021-10-29 17:14:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:44] Number of windows considered: 1...
[2021-10-29 17:14:44] Bias-correcting 1 members separately...
[2021-10-29 17:14:44] Done.
Validation 22, 0 remaining
[2021-10-29 17:14:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:45] Number of windows considered: 1...
[2021-10-29 17:14:45] Bias-correcting 1 members separately...
[2021-10-29 17:14:45] Done.
# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))
index.combinated.rv20max <- MaxReturnValue(wt_conditioned)
[2021-10-29 17:14:46] Performing annual aggregation...
[2021-10-29 17:14:46] Done.
[2021-10-29 17:14:46] - Computing climatology...
[2021-10-29 17:14:46] - Done.
index.combinated <- c(index.combinated, index.combinated.rv20max)
index.eqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.eqm <- c(index.eqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.eqm.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:14:46] Performing annual aggregation...
[2021-10-29 17:14:46] Done.
[2021-10-29 17:14:46] - Computing climatology...
[2021-10-29 17:14:46] - Done.
index.eqm<- c(index.eqm ,index.eqm.rv20max)
index.eqm
Skewness SDII R10 R10p R20 R20p P98Wet
6.929276e+00 1.246739e+01 1.028130e-01 2.403169e+04 5.551407e-02 1.852900e+04 6.864984e+01
P98WetAmount RV20_max
4.925652e+03 1.774268e+02
diff.conditioned <- abs(index.obs-index.combinated)
diff.eqm <- abs(index.obs-index.eqm)
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
score.combinated <- c()
for (i in c(1:9)) {
score.combinated <- c(score.combinated, norm.vector[[i]][5])
}
score.combinated <- mean(score.combinated)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
Combined EQM-C PQM-C GPQM-C GPQM2-C
0.9260063 0.8856119 0.6584010 0.3267997 0.3204339
df <- data.frame(index.obs, index.combinated, index.eqm)
colnames(df) <- c("Observation","Conditioned", "EQM")
format(df, digits = 3, scientific = 5)
bias.df <- data.frame(diff.conditioned, diff.eqm)
colnames(bias.df) <- c("Bias Conditioned", "Bias EQM")
format(bias.df, digits = 3, scientific = 5)
df.st1 <- df
bias.df.st1 <- bias.df
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100
names(bias.rel.cond) <- names(diff.conditioned)
bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100
names(bias.rel.no.cond) <- names(diff.conditioned)
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)
colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias EQM")
format(bias.rel.df, digits = 3, scientific = 5)
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))
abline(a = 0, b = 1)
station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))
points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))
idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))
station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)
points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)
legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))
grid()

ocean buoy?
i=5
station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
[2021-10-29 17:14:49] Performing annual aggregation...
no non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Inf[2021-10-29 17:14:49] Done.
[2021-10-29 17:14:49] - Computing climatology...
[2021-10-29 17:14:49] - Done.
index.obs <- c(index.obs, index.obs.rv20max)
index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
[2021-10-29 17:14:49] Performing annual aggregation...
[2021-10-29 17:14:49] Done.
[2021-10-29 17:14:49] - Computing climatology...
[2021-10-29 17:14:49] - Done.
index.trmm <- c(index.trmm, index.trmm.rv20max)
WT1
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))
station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
[2021-10-29 17:14:49] Performing annual aggregation...
no non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Inf[2021-10-29 17:14:49] Done.
[2021-10-29 17:14:49] - Computing climatology...
[2021-10-29 17:14:49] - Done.
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)
index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
[2021-10-29 17:14:49] Performing annual aggregation...
[2021-10-29 17:14:49] Done.
[2021-10-29 17:14:49] - Computing climatology...
[2021-10-29 17:14:49] - Done.
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")
station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "pqm",cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:14:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:51] Number of windows considered: 1...
[2021-10-29 17:14:51] Bias-correcting 1 members separately...
[2021-10-29 17:14:51] Done.
Validation 2, 20 remaining
[2021-10-29 17:14:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:52] Number of windows considered: 1...
[2021-10-29 17:14:52] Bias-correcting 1 members separately...
[2021-10-29 17:14:52] Done.
Validation 3, 19 remaining
[2021-10-29 17:14:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:53] Number of windows considered: 1...
[2021-10-29 17:14:53] Bias-correcting 1 members separately...
[2021-10-29 17:14:53] Done.
Validation 4, 18 remaining
[2021-10-29 17:14:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:54] Number of windows considered: 1...
[2021-10-29 17:14:54] Bias-correcting 1 members separately...
[2021-10-29 17:14:54] Done.
Validation 5, 17 remaining
[2021-10-29 17:14:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:55] Number of windows considered: 1...
[2021-10-29 17:14:55] Bias-correcting 1 members separately...
[2021-10-29 17:14:55] Done.
Validation 6, 16 remaining
[2021-10-29 17:14:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:56] Number of windows considered: 1...
[2021-10-29 17:14:56] Bias-correcting 1 members separately...
[2021-10-29 17:14:56] Done.
Validation 7, 15 remaining
[2021-10-29 17:14:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:57] Number of windows considered: 1...
[2021-10-29 17:14:57] Bias-correcting 1 members separately...
[2021-10-29 17:14:57] Done.
Validation 8, 14 remaining
[2021-10-29 17:14:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:58] Number of windows considered: 1...
[2021-10-29 17:14:58] Bias-correcting 1 members separately...
[2021-10-29 17:14:58] Done.
Validation 9, 13 remaining
[2021-10-29 17:14:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:14:59] Number of windows considered: 1...
[2021-10-29 17:14:59] Bias-correcting 1 members separately...
[2021-10-29 17:14:59] Done.
Validation 10, 12 remaining
[2021-10-29 17:15:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:00] Number of windows considered: 1...
[2021-10-29 17:15:00] Bias-correcting 1 members separately...
[2021-10-29 17:15:00] Done.
Validation 11, 11 remaining
[2021-10-29 17:15:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:01] Number of windows considered: 1...
[2021-10-29 17:15:01] Bias-correcting 1 members separately...
[2021-10-29 17:15:01] Done.
Validation 12, 10 remaining
[2021-10-29 17:15:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:02] Number of windows considered: 1...
[2021-10-29 17:15:02] Bias-correcting 1 members separately...
[2021-10-29 17:15:02] Done.
Validation 13, 9 remaining
[2021-10-29 17:15:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:03] Number of windows considered: 1...
[2021-10-29 17:15:03] Bias-correcting 1 members separately...
[2021-10-29 17:15:04] Done.
Validation 14, 8 remaining
[2021-10-29 17:15:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:05] Number of windows considered: 1...
[2021-10-29 17:15:05] Bias-correcting 1 members separately...
[2021-10-29 17:15:05] Done.
Validation 15, 7 remaining
[2021-10-29 17:15:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:06] Number of windows considered: 1...
[2021-10-29 17:15:06] Bias-correcting 1 members separately...
[2021-10-29 17:15:06] Done.
Validation 16, 6 remaining
[2021-10-29 17:15:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:07] Number of windows considered: 1...
[2021-10-29 17:15:07] Bias-correcting 1 members separately...
[2021-10-29 17:15:07] Done.
Validation 17, 5 remaining
[2021-10-29 17:15:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:08] Number of windows considered: 1...
[2021-10-29 17:15:08] Bias-correcting 1 members separately...
[2021-10-29 17:15:08] Done.
Validation 18, 4 remaining
[2021-10-29 17:15:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:09] Number of windows considered: 1...
[2021-10-29 17:15:09] Bias-correcting 1 members separately...
[2021-10-29 17:15:09] Done.
Validation 19, 3 remaining
[2021-10-29 17:15:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:10] Number of windows considered: 1...
[2021-10-29 17:15:10] Bias-correcting 1 members separately...
[2021-10-29 17:15:10] Done.
Validation 20, 2 remaining
[2021-10-29 17:15:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:11] Number of windows considered: 1...
[2021-10-29 17:15:11] Bias-correcting 1 members separately...
[2021-10-29 17:15:11] Done.
Validation 21, 1 remaining
[2021-10-29 17:15:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:12] Number of windows considered: 1...
[2021-10-29 17:15:12] Bias-correcting 1 members separately...
[2021-10-29 17:15:12] Done.
Validation 22, 0 remaining
[2021-10-29 17:15:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:13] Number of windows considered: 1...
[2021-10-29 17:15:13] Bias-correcting 1 members separately...
[2021-10-29 17:15:13] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 17:15:14] Performing annual aggregation...
[2021-10-29 17:15:14] Done.
[2021-10-29 17:15:14] - Computing climatology...
[2021-10-29 17:15:14] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.pqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:15:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:15] Number of windows considered: 1...
[2021-10-29 17:15:15] Bias-correcting 1 members separately...
[2021-10-29 17:15:16] Done.
Validation 2, 20 remaining
[2021-10-29 17:15:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:17] Number of windows considered: 1...
[2021-10-29 17:15:17] Bias-correcting 1 members separately...
[2021-10-29 17:15:17] Done.
Validation 3, 19 remaining
[2021-10-29 17:15:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:18] Number of windows considered: 1...
[2021-10-29 17:15:18] Bias-correcting 1 members separately...
[2021-10-29 17:15:18] Done.
Validation 4, 18 remaining
[2021-10-29 17:15:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:19] Number of windows considered: 1...
[2021-10-29 17:15:19] Bias-correcting 1 members separately...
[2021-10-29 17:15:19] Done.
Validation 5, 17 remaining
[2021-10-29 17:15:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:20] Number of windows considered: 1...
[2021-10-29 17:15:20] Bias-correcting 1 members separately...
[2021-10-29 17:15:20] Done.
Validation 6, 16 remaining
[2021-10-29 17:15:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:22] Number of windows considered: 1...
[2021-10-29 17:15:22] Bias-correcting 1 members separately...
[2021-10-29 17:15:22] Done.
Validation 7, 15 remaining
[2021-10-29 17:15:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:23] Number of windows considered: 1...
[2021-10-29 17:15:23] Bias-correcting 1 members separately...
[2021-10-29 17:15:23] Done.
Validation 8, 14 remaining
[2021-10-29 17:15:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:24] Number of windows considered: 1...
[2021-10-29 17:15:24] Bias-correcting 1 members separately...
[2021-10-29 17:15:24] Done.
Validation 9, 13 remaining
[2021-10-29 17:15:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:25] Number of windows considered: 1...
[2021-10-29 17:15:25] Bias-correcting 1 members separately...
[2021-10-29 17:15:25] Done.
Validation 10, 12 remaining
[2021-10-29 17:15:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:26] Number of windows considered: 1...
[2021-10-29 17:15:26] Bias-correcting 1 members separately...
[2021-10-29 17:15:27] Done.
Validation 11, 11 remaining
[2021-10-29 17:15:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:28] Number of windows considered: 1...
[2021-10-29 17:15:28] Bias-correcting 1 members separately...
[2021-10-29 17:15:28] Done.
Validation 12, 10 remaining
[2021-10-29 17:15:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:29] Number of windows considered: 1...
[2021-10-29 17:15:29] Bias-correcting 1 members separately...
[2021-10-29 17:15:29] Done.
Validation 13, 9 remaining
[2021-10-29 17:15:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:30] Number of windows considered: 1...
[2021-10-29 17:15:30] Bias-correcting 1 members separately...
[2021-10-29 17:15:30] Done.
Validation 14, 8 remaining
[2021-10-29 17:15:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:32] Number of windows considered: 1...
[2021-10-29 17:15:32] Bias-correcting 1 members separately...
[2021-10-29 17:15:32] Done.
Validation 15, 7 remaining
[2021-10-29 17:15:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:33] Number of windows considered: 1...
[2021-10-29 17:15:33] Bias-correcting 1 members separately...
[2021-10-29 17:15:33] Done.
Validation 16, 6 remaining
[2021-10-29 17:15:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:34] Number of windows considered: 1...
[2021-10-29 17:15:34] Bias-correcting 1 members separately...
[2021-10-29 17:15:34] Done.
Validation 17, 5 remaining
[2021-10-29 17:15:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:35] Number of windows considered: 1...
[2021-10-29 17:15:35] Bias-correcting 1 members separately...
[2021-10-29 17:15:35] Done.
Validation 18, 4 remaining
[2021-10-29 17:15:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:36] Number of windows considered: 1...
[2021-10-29 17:15:36] Bias-correcting 1 members separately...
[2021-10-29 17:15:37] Done.
Validation 19, 3 remaining
[2021-10-29 17:15:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:38] Number of windows considered: 1...
[2021-10-29 17:15:38] Bias-correcting 1 members separately...
[2021-10-29 17:15:38] Done.
Validation 20, 2 remaining
[2021-10-29 17:15:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:39] Number of windows considered: 1...
[2021-10-29 17:15:39] Bias-correcting 1 members separately...
[2021-10-29 17:15:39] Done.
Validation 21, 1 remaining
[2021-10-29 17:15:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:40] Number of windows considered: 1...
[2021-10-29 17:15:40] Bias-correcting 1 members separately...
[2021-10-29 17:15:40] Done.
Validation 22, 0 remaining
[2021-10-29 17:15:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:41] Number of windows considered: 1...
[2021-10-29 17:15:41] Bias-correcting 1 members separately...
[2021-10-29 17:15:42] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 17:15:42] Performing annual aggregation...
[2021-10-29 17:15:42] Done.
[2021-10-29 17:15:42] - Computing climatology...
[2021-10-29 17:15:42] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.eqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:15:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:44] Number of windows considered: 1...
[2021-10-29 17:15:44] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:15:44] Done.
Validation 2, 20 remaining
[2021-10-29 17:15:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:45] Number of windows considered: 1...
[2021-10-29 17:15:45] Bias-correcting 1 members separately...
[2021-10-29 17:15:45] Done.
Validation 3, 19 remaining
[2021-10-29 17:15:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:46] Number of windows considered: 1...
[2021-10-29 17:15:46] Bias-correcting 1 members separately...
[2021-10-29 17:15:46] Done.
Validation 4, 18 remaining
[2021-10-29 17:15:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:47] Number of windows considered: 1...
[2021-10-29 17:15:47] Bias-correcting 1 members separately...
[2021-10-29 17:15:48] Done.
Validation 5, 17 remaining
[2021-10-29 17:15:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:49] Number of windows considered: 1...
[2021-10-29 17:15:49] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:15:49] Done.
Validation 6, 16 remaining
[2021-10-29 17:15:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:50] Number of windows considered: 1...
[2021-10-29 17:15:50] Bias-correcting 1 members separately...
[2021-10-29 17:15:50] Done.
Validation 7, 15 remaining
[2021-10-29 17:15:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:51] Number of windows considered: 1...
[2021-10-29 17:15:51] Bias-correcting 1 members separately...
[2021-10-29 17:15:51] Done.
Validation 8, 14 remaining
[2021-10-29 17:15:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:52] Number of windows considered: 1...
[2021-10-29 17:15:52] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:15:53] Done.
Validation 9, 13 remaining
[2021-10-29 17:15:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:54] Number of windows considered: 1...
[2021-10-29 17:15:54] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:15:54] Done.
Validation 10, 12 remaining
[2021-10-29 17:15:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:55] Number of windows considered: 1...
[2021-10-29 17:15:55] Bias-correcting 1 members separately...
[2021-10-29 17:15:55] Done.
Validation 11, 11 remaining
[2021-10-29 17:15:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:56] Number of windows considered: 1...
[2021-10-29 17:15:56] Bias-correcting 1 members separately...
[2021-10-29 17:15:56] Done.
Validation 12, 10 remaining
[2021-10-29 17:15:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:57] Number of windows considered: 1...
[2021-10-29 17:15:57] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:15:57] Done.
Validation 13, 9 remaining
[2021-10-29 17:15:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:15:59] Number of windows considered: 1...
[2021-10-29 17:15:59] Bias-correcting 1 members separately...
[2021-10-29 17:15:59] Done.
Validation 14, 8 remaining
[2021-10-29 17:16:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:00] Number of windows considered: 1...
[2021-10-29 17:16:00] Bias-correcting 1 members separately...
[2021-10-29 17:16:00] Done.
Validation 15, 7 remaining
[2021-10-29 17:16:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:01] Number of windows considered: 1...
[2021-10-29 17:16:01] Bias-correcting 1 members separately...
[2021-10-29 17:16:01] Done.
Validation 16, 6 remaining
[2021-10-29 17:16:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:02] Number of windows considered: 1...
[2021-10-29 17:16:02] Bias-correcting 1 members separately...
[2021-10-29 17:16:03] Done.
Validation 17, 5 remaining
[2021-10-29 17:16:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:04] Number of windows considered: 1...
[2021-10-29 17:16:04] Bias-correcting 1 members separately...
[2021-10-29 17:16:04] Done.
Validation 18, 4 remaining
[2021-10-29 17:16:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:05] Number of windows considered: 1...
[2021-10-29 17:16:05] Bias-correcting 1 members separately...
[2021-10-29 17:16:05] Done.
Validation 19, 3 remaining
[2021-10-29 17:16:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:06] Number of windows considered: 1...
[2021-10-29 17:16:06] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:16:06] Done.
Validation 20, 2 remaining
[2021-10-29 17:16:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:07] Number of windows considered: 1...
[2021-10-29 17:16:07] Bias-correcting 1 members separately...
[2021-10-29 17:16:07] Done.
Validation 21, 1 remaining
[2021-10-29 17:16:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:08] Number of windows considered: 1...
[2021-10-29 17:16:08] Bias-correcting 1 members separately...
[2021-10-29 17:16:08] Done.
Validation 22, 0 remaining
[2021-10-29 17:16:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:09] Number of windows considered: 1...
[2021-10-29 17:16:09] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:16:09] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 17:16:10] Performing annual aggregation...
[2021-10-29 17:16:10] Done.
[2021-10-29 17:16:10] - Computing climatology...
[2021-10-29 17:16:10] - Done.
optimization may not have succeeded
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:16:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:11] Number of windows considered: 1...
[2021-10-29 17:16:11] Bias-correcting 1 members separately...
[2021-10-29 17:16:11] Done.
Validation 2, 20 remaining
[2021-10-29 17:16:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:12] Number of windows considered: 1...
[2021-10-29 17:16:12] Bias-correcting 1 members separately...
[2021-10-29 17:16:12] Done.
Validation 3, 19 remaining
[2021-10-29 17:16:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:13] Number of windows considered: 1...
[2021-10-29 17:16:13] Bias-correcting 1 members separately...
[2021-10-29 17:16:13] Done.
Validation 4, 18 remaining
[2021-10-29 17:16:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:14] Number of windows considered: 1...
[2021-10-29 17:16:14] Bias-correcting 1 members separately...
[2021-10-29 17:16:14] Done.
Validation 5, 17 remaining
[2021-10-29 17:16:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:15] Number of windows considered: 1...
[2021-10-29 17:16:15] Bias-correcting 1 members separately...
[2021-10-29 17:16:15] Done.
Validation 6, 16 remaining
[2021-10-29 17:16:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:16] Number of windows considered: 1...
[2021-10-29 17:16:16] Bias-correcting 1 members separately...
[2021-10-29 17:16:16] Done.
Validation 7, 15 remaining
[2021-10-29 17:16:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:17] Number of windows considered: 1...
[2021-10-29 17:16:17] Bias-correcting 1 members separately...
[2021-10-29 17:16:17] Done.
Validation 8, 14 remaining
[2021-10-29 17:16:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:18] Number of windows considered: 1...
[2021-10-29 17:16:18] Bias-correcting 1 members separately...
[2021-10-29 17:16:18] Done.
Validation 9, 13 remaining
[2021-10-29 17:16:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:19] Number of windows considered: 1...
[2021-10-29 17:16:19] Bias-correcting 1 members separately...
[2021-10-29 17:16:19] Done.
Validation 10, 12 remaining
[2021-10-29 17:16:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:20] Number of windows considered: 1...
[2021-10-29 17:16:20] Bias-correcting 1 members separately...
[2021-10-29 17:16:20] Done.
Validation 11, 11 remaining
[2021-10-29 17:16:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:21] Number of windows considered: 1...
[2021-10-29 17:16:21] Bias-correcting 1 members separately...
[2021-10-29 17:16:21] Done.
Validation 12, 10 remaining
[2021-10-29 17:16:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:22] Number of windows considered: 1...
[2021-10-29 17:16:22] Bias-correcting 1 members separately...
[2021-10-29 17:16:22] Done.
Validation 13, 9 remaining
[2021-10-29 17:16:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:23] Number of windows considered: 1...
[2021-10-29 17:16:23] Bias-correcting 1 members separately...
[2021-10-29 17:16:23] Done.
Validation 14, 8 remaining
[2021-10-29 17:16:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:24] Number of windows considered: 1...
[2021-10-29 17:16:24] Bias-correcting 1 members separately...
[2021-10-29 17:16:24] Done.
Validation 15, 7 remaining
[2021-10-29 17:16:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:25] Number of windows considered: 1...
[2021-10-29 17:16:25] Bias-correcting 1 members separately...
[2021-10-29 17:16:25] Done.
Validation 16, 6 remaining
[2021-10-29 17:16:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:26] Number of windows considered: 1...
[2021-10-29 17:16:26] Bias-correcting 1 members separately...
[2021-10-29 17:16:26] Done.
Validation 17, 5 remaining
[2021-10-29 17:16:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:27] Number of windows considered: 1...
[2021-10-29 17:16:27] Bias-correcting 1 members separately...
[2021-10-29 17:16:27] Done.
Validation 18, 4 remaining
[2021-10-29 17:16:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:28] Number of windows considered: 1...
[2021-10-29 17:16:28] Bias-correcting 1 members separately...
[2021-10-29 17:16:29] Done.
Validation 19, 3 remaining
[2021-10-29 17:16:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:29] Number of windows considered: 1...
[2021-10-29 17:16:29] Bias-correcting 1 members separately...
[2021-10-29 17:16:30] Done.
Validation 20, 2 remaining
[2021-10-29 17:16:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:31] Number of windows considered: 1...
[2021-10-29 17:16:31] Bias-correcting 1 members separately...
[2021-10-29 17:16:31] Done.
Validation 21, 1 remaining
[2021-10-29 17:16:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:31] Number of windows considered: 1...
[2021-10-29 17:16:31] Bias-correcting 1 members separately...
[2021-10-29 17:16:32] Done.
Validation 22, 0 remaining
[2021-10-29 17:16:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:33] Number of windows considered: 1...
[2021-10-29 17:16:33] Bias-correcting 1 members separately...
[2021-10-29 17:16:33] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 17:16:33] Performing annual aggregation...
[2021-10-29 17:16:33] Done.
[2021-10-29 17:16:33] - Computing climatology...
[2021-10-29 17:16:33] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm2.cl1 <- index.cal.station.cl1
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i]))
}
normalization <- function(measure){
measure.norm <- c()
#measure must be a vector with the value of a certain measure of different calibrations
for (i in c(1:length(measure))) {
measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
}
return(measure.norm)
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
scores.st5.wt1 <- scores
WT2
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))
station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
[2021-10-29 17:16:34] Performing annual aggregation...
no non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Inf[2021-10-29 17:16:34] Done.
[2021-10-29 17:16:34] - Computing climatology...
[2021-10-29 17:16:34] - Done.
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)
index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
[2021-10-29 17:16:34] Performing annual aggregation...
[2021-10-29 17:16:34] Done.
[2021-10-29 17:16:34] - Computing climatology...
[2021-10-29 17:16:34] - Done.
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")
station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "pqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-10-29 17:16:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:36] Number of windows considered: 1...
[2021-10-29 17:16:36] Bias-correcting 1 members separately...
[2021-10-29 17:16:36] Done.
Validation 2, 20 remaining
[2021-10-29 17:16:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:36] Number of windows considered: 1...
[2021-10-29 17:16:36] Bias-correcting 1 members separately...
[2021-10-29 17:16:36] Done.
Validation 3, 19 remaining
[2021-10-29 17:16:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:37] Number of windows considered: 1...
[2021-10-29 17:16:37] Bias-correcting 1 members separately...
[2021-10-29 17:16:37] Done.
Validation 4, 18 remaining
[2021-10-29 17:16:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:38] Number of windows considered: 1...
[2021-10-29 17:16:38] Bias-correcting 1 members separately...
[2021-10-29 17:16:38] Done.
Validation 5, 17 remaining
[2021-10-29 17:16:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:39] Number of windows considered: 1...
[2021-10-29 17:16:39] Bias-correcting 1 members separately...
[2021-10-29 17:16:39] Done.
Validation 6, 16 remaining
[2021-10-29 17:16:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:40] Number of windows considered: 1...
[2021-10-29 17:16:40] Bias-correcting 1 members separately...
[2021-10-29 17:16:40] Done.
Validation 7, 15 remaining
[2021-10-29 17:16:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:41] Number of windows considered: 1...
[2021-10-29 17:16:42] Bias-correcting 1 members separately...
[2021-10-29 17:16:42] Done.
Validation 8, 14 remaining
[2021-10-29 17:16:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:43] Number of windows considered: 1...
[2021-10-29 17:16:43] Bias-correcting 1 members separately...
[2021-10-29 17:16:43] Done.
Validation 9, 13 remaining
[2021-10-29 17:16:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:44] Number of windows considered: 1...
[2021-10-29 17:16:44] Bias-correcting 1 members separately...
[2021-10-29 17:16:44] Done.
Validation 10, 12 remaining
[2021-10-29 17:16:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:45] Number of windows considered: 1...
[2021-10-29 17:16:45] Bias-correcting 1 members separately...
[2021-10-29 17:16:45] Done.
Validation 11, 11 remaining
[2021-10-29 17:16:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:46] Number of windows considered: 1...
[2021-10-29 17:16:46] Bias-correcting 1 members separately...
[2021-10-29 17:16:46] Done.
Validation 12, 10 remaining
[2021-10-29 17:16:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:47] Number of windows considered: 1...
[2021-10-29 17:16:47] Bias-correcting 1 members separately...
[2021-10-29 17:16:47] Done.
Validation 13, 9 remaining
[2021-10-29 17:16:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:48] Number of windows considered: 1...
[2021-10-29 17:16:48] Bias-correcting 1 members separately...
[2021-10-29 17:16:48] Done.
Validation 14, 8 remaining
[2021-10-29 17:16:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:49] Number of windows considered: 1...
[2021-10-29 17:16:49] Bias-correcting 1 members separately...
[2021-10-29 17:16:49] Done.
Validation 15, 7 remaining
[2021-10-29 17:16:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:50] Number of windows considered: 1...
[2021-10-29 17:16:50] Bias-correcting 1 members separately...
[2021-10-29 17:16:50] Done.
Validation 16, 6 remaining
[2021-10-29 17:16:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:51] Number of windows considered: 1...
[2021-10-29 17:16:51] Bias-correcting 1 members separately...
[2021-10-29 17:16:51] Done.
Validation 17, 5 remaining
[2021-10-29 17:16:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:52] Number of windows considered: 1...
[2021-10-29 17:16:52] Bias-correcting 1 members separately...
[2021-10-29 17:16:52] Done.
Validation 18, 4 remaining
[2021-10-29 17:16:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:53] Number of windows considered: 1...
[2021-10-29 17:16:53] Bias-correcting 1 members separately...
[2021-10-29 17:16:53] Done.
Validation 19, 3 remaining
[2021-10-29 17:16:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:54] Number of windows considered: 1...
[2021-10-29 17:16:54] Bias-correcting 1 members separately...
[2021-10-29 17:16:54] Done.
Validation 20, 2 remaining
[2021-10-29 17:16:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:55] Number of windows considered: 1...
[2021-10-29 17:16:55] Bias-correcting 1 members separately...
[2021-10-29 17:16:55] Done.
Validation 21, 1 remaining
[2021-10-29 17:16:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:56] Number of windows considered: 1...
[2021-10-29 17:16:56] Bias-correcting 1 members separately...
[2021-10-29 17:16:56] Done.
Validation 22, 0 remaining
[2021-10-29 17:16:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:16:57] Number of windows considered: 1...
[2021-10-29 17:16:57] Bias-correcting 1 members separately...
[2021-10-29 17:16:58] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 17:16:58] Performing annual aggregation...
[2021-10-29 17:16:58] Done.
[2021-10-29 17:16:58] - Computing climatology...
[2021-10-29 17:16:58] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.pqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:16:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:00] Number of windows considered: 1...
[2021-10-29 17:17:00] Bias-correcting 1 members separately...
[2021-10-29 17:17:00] Done.
Validation 2, 20 remaining
[2021-10-29 17:17:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:01] Number of windows considered: 1...
[2021-10-29 17:17:01] Bias-correcting 1 members separately...
[2021-10-29 17:17:01] Done.
Validation 3, 19 remaining
[2021-10-29 17:17:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:02] Number of windows considered: 1...
[2021-10-29 17:17:02] Bias-correcting 1 members separately...
[2021-10-29 17:17:02] Done.
Validation 4, 18 remaining
[2021-10-29 17:17:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:03] Number of windows considered: 1...
[2021-10-29 17:17:03] Bias-correcting 1 members separately...
[2021-10-29 17:17:03] Done.
Validation 5, 17 remaining
[2021-10-29 17:17:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:04] Number of windows considered: 1...
[2021-10-29 17:17:04] Bias-correcting 1 members separately...
[2021-10-29 17:17:04] Done.
Validation 6, 16 remaining
[2021-10-29 17:17:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:05] Number of windows considered: 1...
[2021-10-29 17:17:05] Bias-correcting 1 members separately...
[2021-10-29 17:17:05] Done.
Validation 7, 15 remaining
[2021-10-29 17:17:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:06] Number of windows considered: 1...
[2021-10-29 17:17:06] Bias-correcting 1 members separately...
[2021-10-29 17:17:06] Done.
Validation 8, 14 remaining
[2021-10-29 17:17:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:08] Number of windows considered: 1...
[2021-10-29 17:17:08] Bias-correcting 1 members separately...
[2021-10-29 17:17:08] Done.
Validation 9, 13 remaining
[2021-10-29 17:17:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:09] Number of windows considered: 1...
[2021-10-29 17:17:09] Bias-correcting 1 members separately...
[2021-10-29 17:17:09] Done.
Validation 10, 12 remaining
[2021-10-29 17:17:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:10] Number of windows considered: 1...
[2021-10-29 17:17:10] Bias-correcting 1 members separately...
[2021-10-29 17:17:10] Done.
Validation 11, 11 remaining
[2021-10-29 17:17:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:11] Number of windows considered: 1...
[2021-10-29 17:17:11] Bias-correcting 1 members separately...
[2021-10-29 17:17:11] Done.
Validation 12, 10 remaining
[2021-10-29 17:17:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:12] Number of windows considered: 1...
[2021-10-29 17:17:12] Bias-correcting 1 members separately...
[2021-10-29 17:17:13] Done.
Validation 13, 9 remaining
[2021-10-29 17:17:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:14] Number of windows considered: 1...
[2021-10-29 17:17:14] Bias-correcting 1 members separately...
[2021-10-29 17:17:14] Done.
Validation 14, 8 remaining
[2021-10-29 17:17:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:15] Number of windows considered: 1...
[2021-10-29 17:17:15] Bias-correcting 1 members separately...
[2021-10-29 17:17:15] Done.
Validation 15, 7 remaining
[2021-10-29 17:17:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:16] Number of windows considered: 1...
[2021-10-29 17:17:16] Bias-correcting 1 members separately...
[2021-10-29 17:17:16] Done.
Validation 16, 6 remaining
[2021-10-29 17:17:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:17] Number of windows considered: 1...
[2021-10-29 17:17:17] Bias-correcting 1 members separately...
[2021-10-29 17:17:18] Done.
Validation 17, 5 remaining
[2021-10-29 17:17:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:19] Number of windows considered: 1...
[2021-10-29 17:17:19] Bias-correcting 1 members separately...
[2021-10-29 17:17:19] Done.
Validation 18, 4 remaining
[2021-10-29 17:17:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:20] Number of windows considered: 1...
[2021-10-29 17:17:20] Bias-correcting 1 members separately...
[2021-10-29 17:17:20] Done.
Validation 19, 3 remaining
[2021-10-29 17:17:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:21] Number of windows considered: 1...
[2021-10-29 17:17:21] Bias-correcting 1 members separately...
[2021-10-29 17:17:21] Done.
Validation 20, 2 remaining
[2021-10-29 17:17:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:22] Number of windows considered: 1...
[2021-10-29 17:17:22] Bias-correcting 1 members separately...
[2021-10-29 17:17:22] Done.
Validation 21, 1 remaining
[2021-10-29 17:17:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:23] Number of windows considered: 1...
[2021-10-29 17:17:23] Bias-correcting 1 members separately...
[2021-10-29 17:17:23] Done.
Validation 22, 0 remaining
[2021-10-29 17:17:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:25] Number of windows considered: 1...
[2021-10-29 17:17:25] Bias-correcting 1 members separately...
[2021-10-29 17:17:25] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 17:17:25] Performing annual aggregation...
[2021-10-29 17:17:25] Done.
[2021-10-29 17:17:25] - Computing climatology...
[2021-10-29 17:17:25] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.eqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:17:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:27] Number of windows considered: 1...
[2021-10-29 17:17:27] Bias-correcting 1 members separately...
[2021-10-29 17:17:27] Done.
Validation 2, 20 remaining
[2021-10-29 17:17:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:28] Number of windows considered: 1...
[2021-10-29 17:17:28] Bias-correcting 1 members separately...
[2021-10-29 17:17:28] Done.
Validation 3, 19 remaining
[2021-10-29 17:17:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:30] Number of windows considered: 1...
[2021-10-29 17:17:30] Bias-correcting 1 members separately...
[2021-10-29 17:17:30] Done.
Validation 4, 18 remaining
[2021-10-29 17:17:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:31] Number of windows considered: 1...
[2021-10-29 17:17:31] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:17:31] Done.
Validation 5, 17 remaining
[2021-10-29 17:17:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:32] Number of windows considered: 1...
[2021-10-29 17:17:32] Bias-correcting 1 members separately...
[2021-10-29 17:17:32] Done.
Validation 6, 16 remaining
[2021-10-29 17:17:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:33] Number of windows considered: 1...
[2021-10-29 17:17:33] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:17:33] Done.
Validation 7, 15 remaining
[2021-10-29 17:17:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:34] Number of windows considered: 1...
[2021-10-29 17:17:34] Bias-correcting 1 members separately...
[2021-10-29 17:17:34] Done.
Validation 8, 14 remaining
[2021-10-29 17:17:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:35] Number of windows considered: 1...
[2021-10-29 17:17:35] Bias-correcting 1 members separately...
[2021-10-29 17:17:35] Done.
Validation 9, 13 remaining
[2021-10-29 17:17:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:36] Number of windows considered: 1...
[2021-10-29 17:17:36] Bias-correcting 1 members separately...
[2021-10-29 17:17:36] Done.
Validation 10, 12 remaining
[2021-10-29 17:17:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:37] Number of windows considered: 1...
[2021-10-29 17:17:37] Bias-correcting 1 members separately...
[2021-10-29 17:17:37] Done.
Validation 11, 11 remaining
[2021-10-29 17:17:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:38] Number of windows considered: 1...
[2021-10-29 17:17:38] Bias-correcting 1 members separately...
[2021-10-29 17:17:38] Done.
Validation 12, 10 remaining
[2021-10-29 17:17:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:39] Number of windows considered: 1...
[2021-10-29 17:17:39] Bias-correcting 1 members separately...
[2021-10-29 17:17:39] Done.
Validation 13, 9 remaining
[2021-10-29 17:17:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:40] Number of windows considered: 1...
[2021-10-29 17:17:40] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:17:40] Done.
Validation 14, 8 remaining
[2021-10-29 17:17:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:41] Number of windows considered: 1...
[2021-10-29 17:17:41] Bias-correcting 1 members separately...
[2021-10-29 17:17:41] Done.
Validation 15, 7 remaining
[2021-10-29 17:17:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:41] Number of windows considered: 1...
[2021-10-29 17:17:41] Bias-correcting 1 members separately...
[2021-10-29 17:17:42] Done.
Validation 16, 6 remaining
[2021-10-29 17:17:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:42] Number of windows considered: 1...
[2021-10-29 17:17:42] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:17:43] Done.
Validation 17, 5 remaining
[2021-10-29 17:17:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:43] Number of windows considered: 1...
[2021-10-29 17:17:43] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:17:44] Done.
Validation 18, 4 remaining
[2021-10-29 17:17:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:45] Number of windows considered: 1...
[2021-10-29 17:17:45] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:17:45] Done.
Validation 19, 3 remaining
[2021-10-29 17:17:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:46] Number of windows considered: 1...
[2021-10-29 17:17:46] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:17:46] Done.
Validation 20, 2 remaining
[2021-10-29 17:17:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:47] Number of windows considered: 1...
[2021-10-29 17:17:47] Bias-correcting 1 members separately...
[2021-10-29 17:17:47] Done.
Validation 21, 1 remaining
[2021-10-29 17:17:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:48] Number of windows considered: 1...
[2021-10-29 17:17:48] Bias-correcting 1 members separately...
[2021-10-29 17:17:48] Done.
Validation 22, 0 remaining
[2021-10-29 17:17:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:49] Number of windows considered: 1...
[2021-10-29 17:17:49] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:17:49] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 17:17:50] Performing annual aggregation...
[2021-10-29 17:17:50] Done.
[2021-10-29 17:17:50] - Computing climatology...
[2021-10-29 17:17:50] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:17:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:51] Number of windows considered: 1...
[2021-10-29 17:17:51] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:17:51] Done.
Validation 2, 20 remaining
[2021-10-29 17:17:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:52] Number of windows considered: 1...
[2021-10-29 17:17:52] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:17:52] Done.
Validation 3, 19 remaining
[2021-10-29 17:17:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:53] Number of windows considered: 1...
[2021-10-29 17:17:53] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:17:53] Done.
Validation 4, 18 remaining
[2021-10-29 17:17:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:54] Number of windows considered: 1...
[2021-10-29 17:17:54] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:17:54] Done.
Validation 5, 17 remaining
[2021-10-29 17:17:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:55] Number of windows considered: 1...
[2021-10-29 17:17:55] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:17:55] Done.
Validation 6, 16 remaining
[2021-10-29 17:17:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:56] Number of windows considered: 1...
[2021-10-29 17:17:56] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:17:56] Done.
Validation 7, 15 remaining
[2021-10-29 17:17:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:57] Number of windows considered: 1...
[2021-10-29 17:17:57] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:17:57] Done.
Validation 8, 14 remaining
[2021-10-29 17:17:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:58] Number of windows considered: 1...
[2021-10-29 17:17:58] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:17:58] Done.
Validation 9, 13 remaining
[2021-10-29 17:17:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:17:59] Number of windows considered: 1...
[2021-10-29 17:17:59] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:17:59] Done.
Validation 10, 12 remaining
[2021-10-29 17:18:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:01] Number of windows considered: 1...
[2021-10-29 17:18:01] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:18:01] Done.
Validation 11, 11 remaining
[2021-10-29 17:18:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:02] Number of windows considered: 1...
[2021-10-29 17:18:02] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:18:02] Done.
Validation 12, 10 remaining
[2021-10-29 17:18:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:03] Number of windows considered: 1...
[2021-10-29 17:18:03] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:18:03] Done.
Validation 13, 9 remaining
[2021-10-29 17:18:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:04] Number of windows considered: 1...
[2021-10-29 17:18:04] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:18:04] Done.
Validation 14, 8 remaining
[2021-10-29 17:18:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:05] Number of windows considered: 1...
[2021-10-29 17:18:05] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:18:05] Done.
Validation 15, 7 remaining
[2021-10-29 17:18:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:06] Number of windows considered: 1...
[2021-10-29 17:18:06] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:18:06] Done.
Validation 16, 6 remaining
[2021-10-29 17:18:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:07] Number of windows considered: 1...
[2021-10-29 17:18:07] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:18:07] Done.
Validation 17, 5 remaining
[2021-10-29 17:18:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:08] Number of windows considered: 1...
[2021-10-29 17:18:08] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:18:08] Done.
Validation 18, 4 remaining
[2021-10-29 17:18:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:09] Number of windows considered: 1...
[2021-10-29 17:18:09] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:18:09] Done.
Validation 19, 3 remaining
[2021-10-29 17:18:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:10] Number of windows considered: 1...
[2021-10-29 17:18:10] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:18:10] Done.
Validation 20, 2 remaining
[2021-10-29 17:18:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:11] Number of windows considered: 1...
[2021-10-29 17:18:11] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:18:11] Done.
Validation 21, 1 remaining
[2021-10-29 17:18:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:12] Number of windows considered: 1...
[2021-10-29 17:18:12] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:18:13] Done.
Validation 22, 0 remaining
[2021-10-29 17:18:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:14] Number of windows considered: 1...
[2021-10-29 17:18:14] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:18:14] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 17:18:14] Performing annual aggregation...
[2021-10-29 17:18:14] Done.
[2021-10-29 17:18:14] - Computing climatology...
[2021-10-29 17:18:14] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm2.cl2 <- index.cal.station.cl2
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores
EQM-WT2 GPQM2-WT2 PQM-WT2 GPQM-WT2
0.8745978 0.8367691 0.8272098 0.1077562
scores.st5.wt2 <- scores
WT3
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))
station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
[2021-10-29 17:18:15] Performing annual aggregation...
no non-missing arguments to max; returning -Inf[2021-10-29 17:18:15] Done.
[2021-10-29 17:18:15] - Computing climatology...
[2021-10-29 17:18:15] - Done.
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)
index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
[2021-10-29 17:18:15] Performing annual aggregation...
[2021-10-29 17:18:15] Done.
[2021-10-29 17:18:15] - Computing climatology...
[2021-10-29 17:18:15] - Done.
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")
station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:18:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:17] Number of windows considered: 1...
[2021-10-29 17:18:17] Bias-correcting 1 members separately...
[2021-10-29 17:18:17] Done.
Validation 2, 20 remaining
[2021-10-29 17:18:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:18] Number of windows considered: 1...
[2021-10-29 17:18:18] Bias-correcting 1 members separately...
[2021-10-29 17:18:18] Done.
Validation 3, 19 remaining
[2021-10-29 17:18:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:19] Number of windows considered: 1...
[2021-10-29 17:18:19] Bias-correcting 1 members separately...
[2021-10-29 17:18:19] Done.
Validation 4, 18 remaining
[2021-10-29 17:18:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:20] Number of windows considered: 1...
[2021-10-29 17:18:20] Bias-correcting 1 members separately...
[2021-10-29 17:18:20] Done.
Validation 5, 17 remaining
[2021-10-29 17:18:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:21] Number of windows considered: 1...
[2021-10-29 17:18:21] Bias-correcting 1 members separately...
[2021-10-29 17:18:21] Done.
Validation 6, 16 remaining
[2021-10-29 17:18:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:22] Number of windows considered: 1...
[2021-10-29 17:18:22] Bias-correcting 1 members separately...
[2021-10-29 17:18:22] Done.
Validation 7, 15 remaining
[2021-10-29 17:18:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:24] Number of windows considered: 1...
[2021-10-29 17:18:24] Bias-correcting 1 members separately...
[2021-10-29 17:18:24] Done.
Validation 8, 14 remaining
[2021-10-29 17:18:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:25] Number of windows considered: 1...
[2021-10-29 17:18:25] Bias-correcting 1 members separately...
[2021-10-29 17:18:25] Done.
Validation 9, 13 remaining
[2021-10-29 17:18:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:26] Number of windows considered: 1...
[2021-10-29 17:18:26] Bias-correcting 1 members separately...
[2021-10-29 17:18:26] Done.
Validation 10, 12 remaining
[2021-10-29 17:18:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:27] Number of windows considered: 1...
[2021-10-29 17:18:27] Bias-correcting 1 members separately...
[2021-10-29 17:18:27] Done.
Validation 11, 11 remaining
[2021-10-29 17:18:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:28] Number of windows considered: 1...
[2021-10-29 17:18:28] Bias-correcting 1 members separately...
[2021-10-29 17:18:28] Done.
Validation 12, 10 remaining
[2021-10-29 17:18:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:30] Number of windows considered: 1...
[2021-10-29 17:18:30] Bias-correcting 1 members separately...
[2021-10-29 17:18:30] Done.
Validation 13, 9 remaining
[2021-10-29 17:18:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:31] Number of windows considered: 1...
[2021-10-29 17:18:31] Bias-correcting 1 members separately...
[2021-10-29 17:18:31] Done.
Validation 14, 8 remaining
[2021-10-29 17:18:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:32] Number of windows considered: 1...
[2021-10-29 17:18:32] Bias-correcting 1 members separately...
[2021-10-29 17:18:32] Done.
Validation 15, 7 remaining
[2021-10-29 17:18:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:33] Number of windows considered: 1...
[2021-10-29 17:18:33] Bias-correcting 1 members separately...
[2021-10-29 17:18:34] Done.
Validation 16, 6 remaining
[2021-10-29 17:18:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:35] Number of windows considered: 1...
[2021-10-29 17:18:35] Bias-correcting 1 members separately...
[2021-10-29 17:18:35] Done.
Validation 17, 5 remaining
[2021-10-29 17:18:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:36] Number of windows considered: 1...
[2021-10-29 17:18:36] Bias-correcting 1 members separately...
[2021-10-29 17:18:36] Done.
Validation 18, 4 remaining
[2021-10-29 17:18:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:37] Number of windows considered: 1...
[2021-10-29 17:18:37] Bias-correcting 1 members separately...
[2021-10-29 17:18:37] Done.
Validation 19, 3 remaining
[2021-10-29 17:18:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:38] Number of windows considered: 1...
[2021-10-29 17:18:38] Bias-correcting 1 members separately...
[2021-10-29 17:18:38] Done.
Validation 20, 2 remaining
[2021-10-29 17:18:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:40] Number of windows considered: 1...
[2021-10-29 17:18:40] Bias-correcting 1 members separately...
[2021-10-29 17:18:40] Done.
Validation 21, 1 remaining
[2021-10-29 17:18:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:41] Number of windows considered: 1...
[2021-10-29 17:18:41] Bias-correcting 1 members separately...
[2021-10-29 17:18:41] Done.
Validation 22, 0 remaining
[2021-10-29 17:18:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:42] Number of windows considered: 1...
[2021-10-29 17:18:42] Bias-correcting 1 members separately...
[2021-10-29 17:18:42] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 17:18:43] Performing annual aggregation...
[2021-10-29 17:18:43] Done.
[2021-10-29 17:18:43] - Computing climatology...
[2021-10-29 17:18:43] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.pqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:18:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:44] Number of windows considered: 1...
[2021-10-29 17:18:44] Bias-correcting 1 members separately...
[2021-10-29 17:18:44] Done.
Validation 2, 20 remaining
[2021-10-29 17:18:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:45] Number of windows considered: 1...
[2021-10-29 17:18:45] Bias-correcting 1 members separately...
[2021-10-29 17:18:46] Done.
Validation 3, 19 remaining
[2021-10-29 17:18:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:47] Number of windows considered: 1...
[2021-10-29 17:18:47] Bias-correcting 1 members separately...
[2021-10-29 17:18:47] Done.
Validation 4, 18 remaining
[2021-10-29 17:18:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:48] Number of windows considered: 1...
[2021-10-29 17:18:48] Bias-correcting 1 members separately...
[2021-10-29 17:18:48] Done.
Validation 5, 17 remaining
[2021-10-29 17:18:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:49] Number of windows considered: 1...
[2021-10-29 17:18:49] Bias-correcting 1 members separately...
[2021-10-29 17:18:49] Done.
Validation 6, 16 remaining
[2021-10-29 17:18:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:51] Number of windows considered: 1...
[2021-10-29 17:18:51] Bias-correcting 1 members separately...
[2021-10-29 17:18:51] Done.
Validation 7, 15 remaining
[2021-10-29 17:18:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:52] Number of windows considered: 1...
[2021-10-29 17:18:52] Bias-correcting 1 members separately...
[2021-10-29 17:18:52] Done.
Validation 8, 14 remaining
[2021-10-29 17:18:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:53] Number of windows considered: 1...
[2021-10-29 17:18:53] Bias-correcting 1 members separately...
[2021-10-29 17:18:53] Done.
Validation 9, 13 remaining
[2021-10-29 17:18:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:54] Number of windows considered: 1...
[2021-10-29 17:18:54] Bias-correcting 1 members separately...
[2021-10-29 17:18:55] Done.
Validation 10, 12 remaining
[2021-10-29 17:18:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:56] Number of windows considered: 1...
[2021-10-29 17:18:56] Bias-correcting 1 members separately...
[2021-10-29 17:18:56] Done.
Validation 11, 11 remaining
[2021-10-29 17:18:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:57] Number of windows considered: 1...
[2021-10-29 17:18:57] Bias-correcting 1 members separately...
[2021-10-29 17:18:57] Done.
Validation 12, 10 remaining
[2021-10-29 17:18:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:18:58] Number of windows considered: 1...
[2021-10-29 17:18:58] Bias-correcting 1 members separately...
[2021-10-29 17:18:59] Done.
Validation 13, 9 remaining
[2021-10-29 17:19:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:00] Number of windows considered: 1...
[2021-10-29 17:19:00] Bias-correcting 1 members separately...
[2021-10-29 17:19:00] Done.
Validation 14, 8 remaining
[2021-10-29 17:19:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:01] Number of windows considered: 1...
[2021-10-29 17:19:01] Bias-correcting 1 members separately...
[2021-10-29 17:19:01] Done.
Validation 15, 7 remaining
[2021-10-29 17:19:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:02] Number of windows considered: 1...
[2021-10-29 17:19:02] Bias-correcting 1 members separately...
[2021-10-29 17:19:02] Done.
Validation 16, 6 remaining
[2021-10-29 17:19:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:04] Number of windows considered: 1...
[2021-10-29 17:19:04] Bias-correcting 1 members separately...
[2021-10-29 17:19:04] Done.
Validation 17, 5 remaining
[2021-10-29 17:19:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:05] Number of windows considered: 1...
[2021-10-29 17:19:05] Bias-correcting 1 members separately...
[2021-10-29 17:19:05] Done.
Validation 18, 4 remaining
[2021-10-29 17:19:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:06] Number of windows considered: 1...
[2021-10-29 17:19:06] Bias-correcting 1 members separately...
[2021-10-29 17:19:06] Done.
Validation 19, 3 remaining
[2021-10-29 17:19:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:08] Number of windows considered: 1...
[2021-10-29 17:19:08] Bias-correcting 1 members separately...
[2021-10-29 17:19:08] Done.
Validation 20, 2 remaining
[2021-10-29 17:19:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:09] Number of windows considered: 1...
[2021-10-29 17:19:09] Bias-correcting 1 members separately...
[2021-10-29 17:19:09] Done.
Validation 21, 1 remaining
[2021-10-29 17:19:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:10] Number of windows considered: 1...
[2021-10-29 17:19:10] Bias-correcting 1 members separately...
[2021-10-29 17:19:10] Done.
Validation 22, 0 remaining
[2021-10-29 17:19:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:11] Number of windows considered: 1...
[2021-10-29 17:19:11] Bias-correcting 1 members separately...
[2021-10-29 17:19:11] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 17:19:11] Performing annual aggregation...
[2021-10-29 17:19:11] Done.
[2021-10-29 17:19:11] - Computing climatology...
[2021-10-29 17:19:11] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.eqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:19:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:12] Number of windows considered: 1...
[2021-10-29 17:19:12] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:19:13] Done.
Validation 2, 20 remaining
[2021-10-29 17:19:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:13] Number of windows considered: 1...
[2021-10-29 17:19:13] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:14] Done.
Validation 3, 19 remaining
[2021-10-29 17:19:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:14] Number of windows considered: 1...
[2021-10-29 17:19:14] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:14] Done.
Validation 4, 18 remaining
[2021-10-29 17:19:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:15] Number of windows considered: 1...
[2021-10-29 17:19:15] Bias-correcting 1 members separately...
NaNs producedoptimization may not have succeeded[2021-10-29 17:19:15] Done.
Validation 5, 17 remaining
[2021-10-29 17:19:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:16] Number of windows considered: 1...
[2021-10-29 17:19:16] Bias-correcting 1 members separately...
NaNs producedoptimization may not have succeeded[2021-10-29 17:19:16] Done.
Validation 6, 16 remaining
[2021-10-29 17:19:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:17] Number of windows considered: 1...
[2021-10-29 17:19:17] Bias-correcting 1 members separately...
NaNs producedoptimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:19:17] Done.
Validation 7, 15 remaining
[2021-10-29 17:19:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:18] Number of windows considered: 1...
[2021-10-29 17:19:18] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:18] Done.
Validation 8, 14 remaining
[2021-10-29 17:19:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:19] Number of windows considered: 1...
[2021-10-29 17:19:19] Bias-correcting 1 members separately...
NaNs producedoptimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:19:20] Done.
Validation 9, 13 remaining
[2021-10-29 17:19:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:20] Number of windows considered: 1...
[2021-10-29 17:19:20] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:19:21] Done.
Validation 10, 12 remaining
[2021-10-29 17:19:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:21] Number of windows considered: 1...
[2021-10-29 17:19:21] Bias-correcting 1 members separately...
NaNs producedoptimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:19:21] Done.
Validation 11, 11 remaining
[2021-10-29 17:19:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:23] Number of windows considered: 1...
[2021-10-29 17:19:23] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:23] Done.
Validation 12, 10 remaining
[2021-10-29 17:19:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:24] Number of windows considered: 1...
[2021-10-29 17:19:24] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:24] Done.
Validation 13, 9 remaining
[2021-10-29 17:19:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:25] Number of windows considered: 1...
[2021-10-29 17:19:25] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:25] Done.
Validation 14, 8 remaining
[2021-10-29 17:19:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:26] Number of windows considered: 1...
[2021-10-29 17:19:26] Bias-correcting 1 members separately...
NaNs producedoptimization may not have succeeded[2021-10-29 17:19:26] Done.
Validation 15, 7 remaining
[2021-10-29 17:19:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:27] Number of windows considered: 1...
[2021-10-29 17:19:27] Bias-correcting 1 members separately...
NaNs producedoptimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:19:27] Done.
Validation 16, 6 remaining
[2021-10-29 17:19:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:28] Number of windows considered: 1...
[2021-10-29 17:19:28] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:19:28] Done.
Validation 17, 5 remaining
[2021-10-29 17:19:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:29] Number of windows considered: 1...
[2021-10-29 17:19:29] Bias-correcting 1 members separately...
NaNs producedoptimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:19:29] Done.
Validation 18, 4 remaining
[2021-10-29 17:19:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:30] Number of windows considered: 1...
[2021-10-29 17:19:30] Bias-correcting 1 members separately...
NaNs producedoptimization may not have succeeded[2021-10-29 17:19:30] Done.
Validation 19, 3 remaining
[2021-10-29 17:19:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:31] Number of windows considered: 1...
[2021-10-29 17:19:31] Bias-correcting 1 members separately...
NaNs producedoptimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:19:31] Done.
Validation 20, 2 remaining
[2021-10-29 17:19:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:32] Number of windows considered: 1...
[2021-10-29 17:19:32] Bias-correcting 1 members separately...
NaNs producedoptimization may not have succeededno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:19:32] Done.
Validation 21, 1 remaining
[2021-10-29 17:19:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:33] Number of windows considered: 1...
[2021-10-29 17:19:33] Bias-correcting 1 members separately...
NaNs producedoptimization may not have succeeded[2021-10-29 17:19:33] Done.
Validation 22, 0 remaining
[2021-10-29 17:19:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:34] Number of windows considered: 1...
[2021-10-29 17:19:34] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:35] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 17:19:35] Performing annual aggregation...
[2021-10-29 17:19:35] Done.
[2021-10-29 17:19:35] - Computing climatology...
[2021-10-29 17:19:35] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:19:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:36] Number of windows considered: 1...
[2021-10-29 17:19:36] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:36] Done.
Validation 2, 20 remaining
[2021-10-29 17:19:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:37] Number of windows considered: 1...
[2021-10-29 17:19:37] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:37] Done.
Validation 3, 19 remaining
[2021-10-29 17:19:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:38] Number of windows considered: 1...
[2021-10-29 17:19:38] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:38] Done.
Validation 4, 18 remaining
[2021-10-29 17:19:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:39] Number of windows considered: 1...
[2021-10-29 17:19:39] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:39] Done.
Validation 5, 17 remaining
[2021-10-29 17:19:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:40] Number of windows considered: 1...
[2021-10-29 17:19:40] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:40] Done.
Validation 6, 16 remaining
[2021-10-29 17:19:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:41] Number of windows considered: 1...
[2021-10-29 17:19:41] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:41] Done.
Validation 7, 15 remaining
[2021-10-29 17:19:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:42] Number of windows considered: 1...
[2021-10-29 17:19:42] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:43] Done.
Validation 8, 14 remaining
[2021-10-29 17:19:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:44] Number of windows considered: 1...
[2021-10-29 17:19:44] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:44] Done.
Validation 9, 13 remaining
[2021-10-29 17:19:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:45] Number of windows considered: 1...
[2021-10-29 17:19:45] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:45] Done.
Validation 10, 12 remaining
[2021-10-29 17:19:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:46] Number of windows considered: 1...
[2021-10-29 17:19:46] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:46] Done.
Validation 11, 11 remaining
[2021-10-29 17:19:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:47] Number of windows considered: 1...
[2021-10-29 17:19:47] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:47] Done.
Validation 12, 10 remaining
[2021-10-29 17:19:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:48] Number of windows considered: 1...
[2021-10-29 17:19:48] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:48] Done.
Validation 13, 9 remaining
[2021-10-29 17:19:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:49] Number of windows considered: 1...
[2021-10-29 17:19:49] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:49] Done.
Validation 14, 8 remaining
[2021-10-29 17:19:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:50] Number of windows considered: 1...
[2021-10-29 17:19:50] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:50] Done.
Validation 15, 7 remaining
[2021-10-29 17:19:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:51] Number of windows considered: 1...
[2021-10-29 17:19:51] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:51] Done.
Validation 16, 6 remaining
[2021-10-29 17:19:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:52] Number of windows considered: 1...
[2021-10-29 17:19:52] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:52] Done.
Validation 17, 5 remaining
[2021-10-29 17:19:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:53] Number of windows considered: 1...
[2021-10-29 17:19:53] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:53] Done.
Validation 18, 4 remaining
[2021-10-29 17:19:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:54] Number of windows considered: 1...
[2021-10-29 17:19:54] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:54] Done.
Validation 19, 3 remaining
[2021-10-29 17:19:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:55] Number of windows considered: 1...
[2021-10-29 17:19:55] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:55] Done.
Validation 20, 2 remaining
[2021-10-29 17:19:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:56] Number of windows considered: 1...
[2021-10-29 17:19:56] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:56] Done.
Validation 21, 1 remaining
[2021-10-29 17:19:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:57] Number of windows considered: 1...
[2021-10-29 17:19:57] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:58] Done.
Validation 22, 0 remaining
[2021-10-29 17:19:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:19:59] Number of windows considered: 1...
[2021-10-29 17:19:59] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:19:59] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 17:19:59] Performing annual aggregation...
[2021-10-29 17:19:59] Done.
[2021-10-29 17:19:59] - Computing climatology...
[2021-10-29 17:19:59] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm2.cl3 <- index.cal.station.cl3
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
GPQM2-WT3 EQM-WT3 PQM-WT3 GPQM-WT3
0.7347822 0.6435054 0.6319749 0.2151063
scores.st5.wt3 <- scores
WT4
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))
station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
[2021-10-29 17:20:00] Performing annual aggregation...
no non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Inf[2021-10-29 17:20:00] Done.
[2021-10-29 17:20:00] - Computing climatology...
[2021-10-29 17:20:00] - Done.
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)
index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
[2021-10-29 17:20:00] Performing annual aggregation...
[2021-10-29 17:20:00] Done.
[2021-10-29 17:20:00] - Computing climatology...
[2021-10-29 17:20:00] - Done.
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")
station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:20:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:01] Number of windows considered: 1...
[2021-10-29 17:20:01] Bias-correcting 1 members separately...
[2021-10-29 17:20:01] Done.
Validation 2, 20 remaining
[2021-10-29 17:20:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:02] Number of windows considered: 1...
[2021-10-29 17:20:02] Bias-correcting 1 members separately...
[2021-10-29 17:20:02] Done.
Validation 3, 19 remaining
[2021-10-29 17:20:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:03] Number of windows considered: 1...
[2021-10-29 17:20:03] Bias-correcting 1 members separately...
[2021-10-29 17:20:03] Done.
Validation 4, 18 remaining
[2021-10-29 17:20:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:04] Number of windows considered: 1...
[2021-10-29 17:20:04] Bias-correcting 1 members separately...
[2021-10-29 17:20:04] Done.
Validation 5, 17 remaining
[2021-10-29 17:20:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:05] Number of windows considered: 1...
[2021-10-29 17:20:05] Bias-correcting 1 members separately...
[2021-10-29 17:20:05] Done.
Validation 6, 16 remaining
[2021-10-29 17:20:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:06] Number of windows considered: 1...
[2021-10-29 17:20:06] Bias-correcting 1 members separately...
[2021-10-29 17:20:06] Done.
Validation 7, 15 remaining
[2021-10-29 17:20:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:07] Number of windows considered: 1...
[2021-10-29 17:20:07] Bias-correcting 1 members separately...
[2021-10-29 17:20:08] Done.
Validation 8, 14 remaining
[2021-10-29 17:20:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:09] Number of windows considered: 1...
[2021-10-29 17:20:09] Bias-correcting 1 members separately...
[2021-10-29 17:20:09] Done.
Validation 9, 13 remaining
[2021-10-29 17:20:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:10] Number of windows considered: 1...
[2021-10-29 17:20:10] Bias-correcting 1 members separately...
[2021-10-29 17:20:10] Done.
Validation 10, 12 remaining
[2021-10-29 17:20:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:11] Number of windows considered: 1...
[2021-10-29 17:20:11] Bias-correcting 1 members separately...
[2021-10-29 17:20:11] Done.
Validation 11, 11 remaining
[2021-10-29 17:20:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:12] Number of windows considered: 1...
[2021-10-29 17:20:12] Bias-correcting 1 members separately...
[2021-10-29 17:20:12] Done.
Validation 12, 10 remaining
[2021-10-29 17:20:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:13] Number of windows considered: 1...
[2021-10-29 17:20:13] Bias-correcting 1 members separately...
[2021-10-29 17:20:13] Done.
Validation 13, 9 remaining
[2021-10-29 17:20:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:14] Number of windows considered: 1...
[2021-10-29 17:20:14] Bias-correcting 1 members separately...
[2021-10-29 17:20:14] Done.
Validation 14, 8 remaining
[2021-10-29 17:20:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:15] Number of windows considered: 1...
[2021-10-29 17:20:15] Bias-correcting 1 members separately...
[2021-10-29 17:20:15] Done.
Validation 15, 7 remaining
[2021-10-29 17:20:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:17] Number of windows considered: 1...
[2021-10-29 17:20:17] Bias-correcting 1 members separately...
[2021-10-29 17:20:17] Done.
Validation 16, 6 remaining
[2021-10-29 17:20:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:18] Number of windows considered: 1...
[2021-10-29 17:20:18] Bias-correcting 1 members separately...
[2021-10-29 17:20:18] Done.
Validation 17, 5 remaining
[2021-10-29 17:20:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:19] Number of windows considered: 1...
[2021-10-29 17:20:19] Bias-correcting 1 members separately...
[2021-10-29 17:20:19] Done.
Validation 18, 4 remaining
[2021-10-29 17:20:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:20] Number of windows considered: 1...
[2021-10-29 17:20:20] Bias-correcting 1 members separately...
[2021-10-29 17:20:20] Done.
Validation 19, 3 remaining
[2021-10-29 17:20:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:21] Number of windows considered: 1...
[2021-10-29 17:20:21] Bias-correcting 1 members separately...
[2021-10-29 17:20:21] Done.
Validation 20, 2 remaining
[2021-10-29 17:20:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:22] Number of windows considered: 1...
[2021-10-29 17:20:22] Bias-correcting 1 members separately...
[2021-10-29 17:20:22] Done.
Validation 21, 1 remaining
[2021-10-29 17:20:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:23] Number of windows considered: 1...
[2021-10-29 17:20:23] Bias-correcting 1 members separately...
[2021-10-29 17:20:23] Done.
Validation 22, 0 remaining
[2021-10-29 17:20:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:24] Number of windows considered: 1...
[2021-10-29 17:20:24] Bias-correcting 1 members separately...
[2021-10-29 17:20:24] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 17:20:25] Performing annual aggregation...
[2021-10-29 17:20:25] Done.
[2021-10-29 17:20:25] - Computing climatology...
[2021-10-29 17:20:25] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.pqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:20:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:26] Number of windows considered: 1...
[2021-10-29 17:20:26] Bias-correcting 1 members separately...
[2021-10-29 17:20:26] Done.
Validation 2, 20 remaining
[2021-10-29 17:20:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:28] Number of windows considered: 1...
[2021-10-29 17:20:28] Bias-correcting 1 members separately...
[2021-10-29 17:20:28] Done.
Validation 3, 19 remaining
[2021-10-29 17:20:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:29] Number of windows considered: 1...
[2021-10-29 17:20:29] Bias-correcting 1 members separately...
[2021-10-29 17:20:29] Done.
Validation 4, 18 remaining
[2021-10-29 17:20:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:30] Number of windows considered: 1...
[2021-10-29 17:20:30] Bias-correcting 1 members separately...
[2021-10-29 17:20:30] Done.
Validation 5, 17 remaining
[2021-10-29 17:20:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:31] Number of windows considered: 1...
[2021-10-29 17:20:31] Bias-correcting 1 members separately...
[2021-10-29 17:20:31] Done.
Validation 6, 16 remaining
[2021-10-29 17:20:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:33] Number of windows considered: 1...
[2021-10-29 17:20:33] Bias-correcting 1 members separately...
[2021-10-29 17:20:33] Done.
Validation 7, 15 remaining
[2021-10-29 17:20:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:34] Number of windows considered: 1...
[2021-10-29 17:20:34] Bias-correcting 1 members separately...
[2021-10-29 17:20:34] Done.
Validation 8, 14 remaining
[2021-10-29 17:20:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:35] Number of windows considered: 1...
[2021-10-29 17:20:35] Bias-correcting 1 members separately...
[2021-10-29 17:20:36] Done.
Validation 9, 13 remaining
[2021-10-29 17:20:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:37] Number of windows considered: 1...
[2021-10-29 17:20:37] Bias-correcting 1 members separately...
[2021-10-29 17:20:37] Done.
Validation 10, 12 remaining
[2021-10-29 17:20:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:38] Number of windows considered: 1...
[2021-10-29 17:20:38] Bias-correcting 1 members separately...
[2021-10-29 17:20:38] Done.
Validation 11, 11 remaining
[2021-10-29 17:20:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:39] Number of windows considered: 1...
[2021-10-29 17:20:39] Bias-correcting 1 members separately...
[2021-10-29 17:20:39] Done.
Validation 12, 10 remaining
[2021-10-29 17:20:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:41] Number of windows considered: 1...
[2021-10-29 17:20:41] Bias-correcting 1 members separately...
[2021-10-29 17:20:41] Done.
Validation 13, 9 remaining
[2021-10-29 17:20:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:42] Number of windows considered: 1...
[2021-10-29 17:20:42] Bias-correcting 1 members separately...
[2021-10-29 17:20:42] Done.
Validation 14, 8 remaining
[2021-10-29 17:20:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:43] Number of windows considered: 1...
[2021-10-29 17:20:43] Bias-correcting 1 members separately...
[2021-10-29 17:20:43] Done.
Validation 15, 7 remaining
[2021-10-29 17:20:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:45] Number of windows considered: 1...
[2021-10-29 17:20:45] Bias-correcting 1 members separately...
[2021-10-29 17:20:45] Done.
Validation 16, 6 remaining
[2021-10-29 17:20:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:46] Number of windows considered: 1...
[2021-10-29 17:20:46] Bias-correcting 1 members separately...
[2021-10-29 17:20:46] Done.
Validation 17, 5 remaining
[2021-10-29 17:20:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:47] Number of windows considered: 1...
[2021-10-29 17:20:47] Bias-correcting 1 members separately...
[2021-10-29 17:20:47] Done.
Validation 18, 4 remaining
[2021-10-29 17:20:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:48] Number of windows considered: 1...
[2021-10-29 17:20:48] Bias-correcting 1 members separately...
[2021-10-29 17:20:48] Done.
Validation 19, 3 remaining
[2021-10-29 17:20:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:49] Number of windows considered: 1...
[2021-10-29 17:20:49] Bias-correcting 1 members separately...
[2021-10-29 17:20:49] Done.
Validation 20, 2 remaining
[2021-10-29 17:20:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:50] Number of windows considered: 1...
[2021-10-29 17:20:50] Bias-correcting 1 members separately...
[2021-10-29 17:20:50] Done.
Validation 21, 1 remaining
[2021-10-29 17:20:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:51] Number of windows considered: 1...
[2021-10-29 17:20:51] Bias-correcting 1 members separately...
[2021-10-29 17:20:51] Done.
Validation 22, 0 remaining
[2021-10-29 17:20:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:52] Number of windows considered: 1...
[2021-10-29 17:20:52] Bias-correcting 1 members separately...
[2021-10-29 17:20:52] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 17:20:52] Performing annual aggregation...
[2021-10-29 17:20:52] Done.
[2021-10-29 17:20:52] - Computing climatology...
[2021-10-29 17:20:52] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.eqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:20:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:53] Number of windows considered: 1...
[2021-10-29 17:20:53] Bias-correcting 1 members separately...
[2021-10-29 17:20:54] Done.
Validation 2, 20 remaining
[2021-10-29 17:20:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:54] Number of windows considered: 1...
[2021-10-29 17:20:54] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:20:55] Done.
Validation 3, 19 remaining
[2021-10-29 17:20:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:55] Number of windows considered: 1...
[2021-10-29 17:20:55] Bias-correcting 1 members separately...
[2021-10-29 17:20:55] Done.
Validation 4, 18 remaining
[2021-10-29 17:20:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:56] Number of windows considered: 1...
[2021-10-29 17:20:56] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:20:56] Done.
Validation 5, 17 remaining
[2021-10-29 17:20:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:57] Number of windows considered: 1...
[2021-10-29 17:20:57] Bias-correcting 1 members separately...
[2021-10-29 17:20:57] Done.
Validation 6, 16 remaining
[2021-10-29 17:20:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:58] Number of windows considered: 1...
[2021-10-29 17:20:58] Bias-correcting 1 members separately...
optimization may not have succeeded[2021-10-29 17:20:58] Done.
Validation 7, 15 remaining
[2021-10-29 17:20:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:20:59] Number of windows considered: 1...
[2021-10-29 17:20:59] Bias-correcting 1 members separately...
[2021-10-29 17:21:00] Done.
Validation 8, 14 remaining
[2021-10-29 17:21:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:01] Number of windows considered: 1...
[2021-10-29 17:21:01] Bias-correcting 1 members separately...
[2021-10-29 17:21:01] Done.
Validation 9, 13 remaining
[2021-10-29 17:21:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:02] Number of windows considered: 1...
[2021-10-29 17:21:02] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:21:02] Done.
Validation 10, 12 remaining
[2021-10-29 17:21:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:03] Number of windows considered: 1...
[2021-10-29 17:21:03] Bias-correcting 1 members separately...
[2021-10-29 17:21:03] Done.
Validation 11, 11 remaining
[2021-10-29 17:21:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:04] Number of windows considered: 1...
[2021-10-29 17:21:04] Bias-correcting 1 members separately...
[2021-10-29 17:21:04] Done.
Validation 12, 10 remaining
[2021-10-29 17:21:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:05] Number of windows considered: 1...
[2021-10-29 17:21:05] Bias-correcting 1 members separately...
[2021-10-29 17:21:05] Done.
Validation 13, 9 remaining
[2021-10-29 17:21:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:06] Number of windows considered: 1...
[2021-10-29 17:21:06] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:21:06] Done.
Validation 14, 8 remaining
[2021-10-29 17:21:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:07] Number of windows considered: 1...
[2021-10-29 17:21:07] Bias-correcting 1 members separately...
[2021-10-29 17:21:07] Done.
Validation 15, 7 remaining
[2021-10-29 17:21:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:08] Number of windows considered: 1...
[2021-10-29 17:21:08] Bias-correcting 1 members separately...
[2021-10-29 17:21:08] Done.
Validation 16, 6 remaining
[2021-10-29 17:21:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:09] Number of windows considered: 1...
[2021-10-29 17:21:09] Bias-correcting 1 members separately...
[2021-10-29 17:21:09] Done.
Validation 17, 5 remaining
[2021-10-29 17:21:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:10] Number of windows considered: 1...
[2021-10-29 17:21:10] Bias-correcting 1 members separately...
[2021-10-29 17:21:10] Done.
Validation 18, 4 remaining
[2021-10-29 17:21:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:11] Number of windows considered: 1...
[2021-10-29 17:21:11] Bias-correcting 1 members separately...
[2021-10-29 17:21:11] Done.
Validation 19, 3 remaining
[2021-10-29 17:21:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:12] Number of windows considered: 1...
[2021-10-29 17:21:12] Bias-correcting 1 members separately...
[2021-10-29 17:21:12] Done.
Validation 20, 2 remaining
[2021-10-29 17:21:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:13] Number of windows considered: 1...
[2021-10-29 17:21:13] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:21:13] Done.
Validation 21, 1 remaining
[2021-10-29 17:21:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:14] Number of windows considered: 1...
[2021-10-29 17:21:14] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:21:15] Done.
Validation 22, 0 remaining
[2021-10-29 17:21:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:16] Number of windows considered: 1...
[2021-10-29 17:21:16] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:21:16] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 17:21:16] Performing annual aggregation...
[2021-10-29 17:21:16] Done.
[2021-10-29 17:21:16] - Computing climatology...
[2021-10-29 17:21:16] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:21:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:18] Number of windows considered: 1...
[2021-10-29 17:21:18] Bias-correcting 1 members separately...
[2021-10-29 17:21:18] Done.
Validation 2, 20 remaining
[2021-10-29 17:21:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:19] Number of windows considered: 1...
[2021-10-29 17:21:19] Bias-correcting 1 members separately...
[2021-10-29 17:21:19] Done.
Validation 3, 19 remaining
[2021-10-29 17:21:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:20] Number of windows considered: 1...
[2021-10-29 17:21:20] Bias-correcting 1 members separately...
[2021-10-29 17:21:20] Done.
Validation 4, 18 remaining
[2021-10-29 17:21:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:21] Number of windows considered: 1...
[2021-10-29 17:21:21] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:21:21] Done.
Validation 5, 17 remaining
[2021-10-29 17:21:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:22] Number of windows considered: 1...
[2021-10-29 17:21:22] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:21:22] Done.
Validation 6, 16 remaining
[2021-10-29 17:21:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:23] Number of windows considered: 1...
[2021-10-29 17:21:23] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:21:23] Done.
Validation 7, 15 remaining
[2021-10-29 17:21:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:24] Number of windows considered: 1...
[2021-10-29 17:21:24] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:21:24] Done.
Validation 8, 14 remaining
[2021-10-29 17:21:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:25] Number of windows considered: 1...
[2021-10-29 17:21:25] Bias-correcting 1 members separately...
[2021-10-29 17:21:25] Done.
Validation 9, 13 remaining
[2021-10-29 17:21:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:26] Number of windows considered: 1...
[2021-10-29 17:21:26] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:21:26] Done.
Validation 10, 12 remaining
[2021-10-29 17:21:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:27] Number of windows considered: 1...
[2021-10-29 17:21:28] Bias-correcting 1 members separately...
[2021-10-29 17:21:28] Done.
Validation 11, 11 remaining
[2021-10-29 17:21:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:29] Number of windows considered: 1...
[2021-10-29 17:21:29] Bias-correcting 1 members separately...
[2021-10-29 17:21:29] Done.
Validation 12, 10 remaining
[2021-10-29 17:21:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:30] Number of windows considered: 1...
[2021-10-29 17:21:30] Bias-correcting 1 members separately...
[2021-10-29 17:21:30] Done.
Validation 13, 9 remaining
[2021-10-29 17:21:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:31] Number of windows considered: 1...
[2021-10-29 17:21:31] Bias-correcting 1 members separately...
[2021-10-29 17:21:31] Done.
Validation 14, 8 remaining
[2021-10-29 17:21:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:32] Number of windows considered: 1...
[2021-10-29 17:21:32] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:21:32] Done.
Validation 15, 7 remaining
[2021-10-29 17:21:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:33] Number of windows considered: 1...
[2021-10-29 17:21:33] Bias-correcting 1 members separately...
[2021-10-29 17:21:33] Done.
Validation 16, 6 remaining
[2021-10-29 17:21:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:35] Number of windows considered: 1...
[2021-10-29 17:21:35] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:21:35] Done.
Validation 17, 5 remaining
[2021-10-29 17:21:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:36] Number of windows considered: 1...
[2021-10-29 17:21:36] Bias-correcting 1 members separately...
[2021-10-29 17:21:36] Done.
Validation 18, 4 remaining
[2021-10-29 17:21:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:37] Number of windows considered: 1...
[2021-10-29 17:21:37] Bias-correcting 1 members separately...
[2021-10-29 17:21:37] Done.
Validation 19, 3 remaining
[2021-10-29 17:21:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:38] Number of windows considered: 1...
[2021-10-29 17:21:38] Bias-correcting 1 members separately...
[2021-10-29 17:21:38] Done.
Validation 20, 2 remaining
[2021-10-29 17:21:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:39] Number of windows considered: 1...
[2021-10-29 17:21:39] Bias-correcting 1 members separately...
[2021-10-29 17:21:39] Done.
Validation 21, 1 remaining
[2021-10-29 17:21:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:41] Number of windows considered: 1...
[2021-10-29 17:21:41] Bias-correcting 1 members separately...
[2021-10-29 17:21:41] Done.
Validation 22, 0 remaining
[2021-10-29 17:21:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:42] Number of windows considered: 1...
[2021-10-29 17:21:42] Bias-correcting 1 members separately...
[2021-10-29 17:21:42] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 17:21:42] Performing annual aggregation...
[2021-10-29 17:21:42] Done.
[2021-10-29 17:21:42] - Computing climatology...
[2021-10-29 17:21:42] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm2.cl4 <- index.cal.station.cl4
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)
scores
PQM-WT4 EQM-WT4 GPQM2-WT4 GPQM-WT4
0.7952446 0.4633320 0.3948906 0.3093824
scores.st5.wt4 <- scores
WT5
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))
station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
[2021-10-29 17:21:43] Performing annual aggregation...
no non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Inf[2021-10-29 17:21:43] Done.
[2021-10-29 17:21:43] - Computing climatology...
[2021-10-29 17:21:43] - Done.
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)
index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
[2021-10-29 17:21:43] Performing annual aggregation...
[2021-10-29 17:21:43] Done.
[2021-10-29 17:21:43] - Computing climatology...
[2021-10-29 17:21:43] - Done.
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")
station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:21:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:45] Number of windows considered: 1...
[2021-10-29 17:21:45] Bias-correcting 1 members separately...
[2021-10-29 17:21:45] Done.
Validation 2, 20 remaining
[2021-10-29 17:21:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:46] Number of windows considered: 1...
[2021-10-29 17:21:46] Bias-correcting 1 members separately...
[2021-10-29 17:21:46] Done.
Validation 3, 19 remaining
[2021-10-29 17:21:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:47] Number of windows considered: 1...
[2021-10-29 17:21:47] Bias-correcting 1 members separately...
[2021-10-29 17:21:47] Done.
Validation 4, 18 remaining
[2021-10-29 17:21:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:48] Number of windows considered: 1...
[2021-10-29 17:21:48] Bias-correcting 1 members separately...
[2021-10-29 17:21:48] Done.
Validation 5, 17 remaining
[2021-10-29 17:21:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:49] Number of windows considered: 1...
[2021-10-29 17:21:49] Bias-correcting 1 members separately...
[2021-10-29 17:21:49] Done.
Validation 6, 16 remaining
[2021-10-29 17:21:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:50] Number of windows considered: 1...
[2021-10-29 17:21:50] Bias-correcting 1 members separately...
[2021-10-29 17:21:50] Done.
Validation 7, 15 remaining
[2021-10-29 17:21:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:51] Number of windows considered: 1...
[2021-10-29 17:21:51] Bias-correcting 1 members separately...
[2021-10-29 17:21:51] Done.
Validation 8, 14 remaining
[2021-10-29 17:21:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:53] Number of windows considered: 1...
[2021-10-29 17:21:53] Bias-correcting 1 members separately...
[2021-10-29 17:21:53] Done.
Validation 9, 13 remaining
[2021-10-29 17:21:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:54] Number of windows considered: 1...
[2021-10-29 17:21:54] Bias-correcting 1 members separately...
[2021-10-29 17:21:54] Done.
Validation 10, 12 remaining
[2021-10-29 17:21:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:55] Number of windows considered: 1...
[2021-10-29 17:21:55] Bias-correcting 1 members separately...
[2021-10-29 17:21:55] Done.
Validation 11, 11 remaining
[2021-10-29 17:21:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:56] Number of windows considered: 1...
[2021-10-29 17:21:56] Bias-correcting 1 members separately...
[2021-10-29 17:21:56] Done.
Validation 12, 10 remaining
[2021-10-29 17:21:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:57] Number of windows considered: 1...
[2021-10-29 17:21:57] Bias-correcting 1 members separately...
[2021-10-29 17:21:57] Done.
Validation 13, 9 remaining
[2021-10-29 17:21:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:21:58] Number of windows considered: 1...
[2021-10-29 17:21:58] Bias-correcting 1 members separately...
[2021-10-29 17:21:58] Done.
Validation 14, 8 remaining
[2021-10-29 17:22:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:00] Number of windows considered: 1...
[2021-10-29 17:22:00] Bias-correcting 1 members separately...
[2021-10-29 17:22:00] Done.
Validation 15, 7 remaining
[2021-10-29 17:22:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:01] Number of windows considered: 1...
[2021-10-29 17:22:01] Bias-correcting 1 members separately...
[2021-10-29 17:22:01] Done.
Validation 16, 6 remaining
[2021-10-29 17:22:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:02] Number of windows considered: 1...
[2021-10-29 17:22:02] Bias-correcting 1 members separately...
[2021-10-29 17:22:02] Done.
Validation 17, 5 remaining
[2021-10-29 17:22:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:03] Number of windows considered: 1...
[2021-10-29 17:22:03] Bias-correcting 1 members separately...
[2021-10-29 17:22:03] Done.
Validation 18, 4 remaining
[2021-10-29 17:22:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:04] Number of windows considered: 1...
[2021-10-29 17:22:04] Bias-correcting 1 members separately...
[2021-10-29 17:22:04] Done.
Validation 19, 3 remaining
[2021-10-29 17:22:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:06] Number of windows considered: 1...
[2021-10-29 17:22:06] Bias-correcting 1 members separately...
[2021-10-29 17:22:06] Done.
Validation 20, 2 remaining
[2021-10-29 17:22:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:07] Number of windows considered: 1...
[2021-10-29 17:22:07] Bias-correcting 1 members separately...
[2021-10-29 17:22:07] Done.
Validation 21, 1 remaining
[2021-10-29 17:22:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:08] Number of windows considered: 1...
[2021-10-29 17:22:08] Bias-correcting 1 members separately...
[2021-10-29 17:22:08] Done.
Validation 22, 0 remaining
[2021-10-29 17:22:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:09] Number of windows considered: 1...
[2021-10-29 17:22:09] Bias-correcting 1 members separately...
[2021-10-29 17:22:09] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 17:22:10] Performing annual aggregation...
[2021-10-29 17:22:10] Done.
[2021-10-29 17:22:10] - Computing climatology...
[2021-10-29 17:22:10] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.pqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:22:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:11] Number of windows considered: 1...
[2021-10-29 17:22:11] Bias-correcting 1 members separately...
[2021-10-29 17:22:11] Done.
Validation 2, 20 remaining
[2021-10-29 17:22:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:12] Number of windows considered: 1...
[2021-10-29 17:22:12] Bias-correcting 1 members separately...
[2021-10-29 17:22:12] Done.
Validation 3, 19 remaining
[2021-10-29 17:22:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:13] Number of windows considered: 1...
[2021-10-29 17:22:13] Bias-correcting 1 members separately...
[2021-10-29 17:22:13] Done.
Validation 4, 18 remaining
[2021-10-29 17:22:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:14] Number of windows considered: 1...
[2021-10-29 17:22:14] Bias-correcting 1 members separately...
[2021-10-29 17:22:14] Done.
Validation 5, 17 remaining
[2021-10-29 17:22:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:15] Number of windows considered: 1...
[2021-10-29 17:22:15] Bias-correcting 1 members separately...
[2021-10-29 17:22:15] Done.
Validation 6, 16 remaining
[2021-10-29 17:22:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:16] Number of windows considered: 1...
[2021-10-29 17:22:16] Bias-correcting 1 members separately...
[2021-10-29 17:22:16] Done.
Validation 7, 15 remaining
[2021-10-29 17:22:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:17] Number of windows considered: 1...
[2021-10-29 17:22:17] Bias-correcting 1 members separately...
[2021-10-29 17:22:17] Done.
Validation 8, 14 remaining
[2021-10-29 17:22:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:18] Number of windows considered: 1...
[2021-10-29 17:22:18] Bias-correcting 1 members separately...
[2021-10-29 17:22:18] Done.
Validation 9, 13 remaining
[2021-10-29 17:22:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:19] Number of windows considered: 1...
[2021-10-29 17:22:19] Bias-correcting 1 members separately...
[2021-10-29 17:22:19] Done.
Validation 10, 12 remaining
[2021-10-29 17:22:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:20] Number of windows considered: 1...
[2021-10-29 17:22:20] Bias-correcting 1 members separately...
[2021-10-29 17:22:20] Done.
Validation 11, 11 remaining
[2021-10-29 17:22:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:21] Number of windows considered: 1...
[2021-10-29 17:22:21] Bias-correcting 1 members separately...
[2021-10-29 17:22:21] Done.
Validation 12, 10 remaining
[2021-10-29 17:22:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:22] Number of windows considered: 1...
[2021-10-29 17:22:22] Bias-correcting 1 members separately...
[2021-10-29 17:22:22] Done.
Validation 13, 9 remaining
[2021-10-29 17:22:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:23] Number of windows considered: 1...
[2021-10-29 17:22:23] Bias-correcting 1 members separately...
[2021-10-29 17:22:23] Done.
Validation 14, 8 remaining
[2021-10-29 17:22:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:24] Number of windows considered: 1...
[2021-10-29 17:22:24] Bias-correcting 1 members separately...
[2021-10-29 17:22:25] Done.
Validation 15, 7 remaining
[2021-10-29 17:22:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:25] Number of windows considered: 1...
[2021-10-29 17:22:25] Bias-correcting 1 members separately...
[2021-10-29 17:22:26] Done.
Validation 16, 6 remaining
[2021-10-29 17:22:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:27] Number of windows considered: 1...
[2021-10-29 17:22:27] Bias-correcting 1 members separately...
[2021-10-29 17:22:27] Done.
Validation 17, 5 remaining
[2021-10-29 17:22:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:28] Number of windows considered: 1...
[2021-10-29 17:22:28] Bias-correcting 1 members separately...
[2021-10-29 17:22:28] Done.
Validation 18, 4 remaining
[2021-10-29 17:22:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:29] Number of windows considered: 1...
[2021-10-29 17:22:29] Bias-correcting 1 members separately...
[2021-10-29 17:22:29] Done.
Validation 19, 3 remaining
[2021-10-29 17:22:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:30] Number of windows considered: 1...
[2021-10-29 17:22:30] Bias-correcting 1 members separately...
[2021-10-29 17:22:30] Done.
Validation 20, 2 remaining
[2021-10-29 17:22:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:31] Number of windows considered: 1...
[2021-10-29 17:22:31] Bias-correcting 1 members separately...
[2021-10-29 17:22:31] Done.
Validation 21, 1 remaining
[2021-10-29 17:22:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:32] Number of windows considered: 1...
[2021-10-29 17:22:32] Bias-correcting 1 members separately...
[2021-10-29 17:22:32] Done.
Validation 22, 0 remaining
[2021-10-29 17:22:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:33] Number of windows considered: 1...
[2021-10-29 17:22:33] Bias-correcting 1 members separately...
[2021-10-29 17:22:33] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 17:22:34] Performing annual aggregation...
[2021-10-29 17:22:34] Done.
[2021-10-29 17:22:34] - Computing climatology...
[2021-10-29 17:22:34] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.eqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:22:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:35] Number of windows considered: 1...
[2021-10-29 17:22:35] Bias-correcting 1 members separately...
[2021-10-29 17:22:35] Done.
Validation 2, 20 remaining
[2021-10-29 17:22:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:36] Number of windows considered: 1...
[2021-10-29 17:22:36] Bias-correcting 1 members separately...
[2021-10-29 17:22:37] Done.
Validation 3, 19 remaining
[2021-10-29 17:22:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:38] Number of windows considered: 1...
[2021-10-29 17:22:38] Bias-correcting 1 members separately...
[2021-10-29 17:22:38] Done.
Validation 4, 18 remaining
[2021-10-29 17:22:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:39] Number of windows considered: 1...
[2021-10-29 17:22:39] Bias-correcting 1 members separately...
[2021-10-29 17:22:39] Done.
Validation 5, 17 remaining
[2021-10-29 17:22:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:40] Number of windows considered: 1...
[2021-10-29 17:22:40] Bias-correcting 1 members separately...
[2021-10-29 17:22:40] Done.
Validation 6, 16 remaining
[2021-10-29 17:22:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:41] Number of windows considered: 1...
[2021-10-29 17:22:41] Bias-correcting 1 members separately...
[2021-10-29 17:22:41] Done.
Validation 7, 15 remaining
[2021-10-29 17:22:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:42] Number of windows considered: 1...
[2021-10-29 17:22:42] Bias-correcting 1 members separately...
[2021-10-29 17:22:42] Done.
Validation 8, 14 remaining
[2021-10-29 17:22:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:43] Number of windows considered: 1...
[2021-10-29 17:22:43] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:22:43] Done.
Validation 9, 13 remaining
[2021-10-29 17:22:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:44] Number of windows considered: 1...
[2021-10-29 17:22:44] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:22:44] Done.
Validation 10, 12 remaining
[2021-10-29 17:22:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:45] Number of windows considered: 1...
[2021-10-29 17:22:45] Bias-correcting 1 members separately...
[2021-10-29 17:22:45] Done.
Validation 11, 11 remaining
[2021-10-29 17:22:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:46] Number of windows considered: 1...
[2021-10-29 17:22:46] Bias-correcting 1 members separately...
[2021-10-29 17:22:47] Done.
Validation 12, 10 remaining
[2021-10-29 17:22:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:47] Number of windows considered: 1...
[2021-10-29 17:22:47] Bias-correcting 1 members separately...
[2021-10-29 17:22:48] Done.
Validation 13, 9 remaining
[2021-10-29 17:22:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:49] Number of windows considered: 1...
[2021-10-29 17:22:49] Bias-correcting 1 members separately...
[2021-10-29 17:22:49] Done.
Validation 14, 8 remaining
[2021-10-29 17:22:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:50] Number of windows considered: 1...
[2021-10-29 17:22:50] Bias-correcting 1 members separately...
[2021-10-29 17:22:50] Done.
Validation 15, 7 remaining
[2021-10-29 17:22:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:51] Number of windows considered: 1...
[2021-10-29 17:22:51] Bias-correcting 1 members separately...
[2021-10-29 17:22:51] Done.
Validation 16, 6 remaining
[2021-10-29 17:22:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:52] Number of windows considered: 1...
[2021-10-29 17:22:52] Bias-correcting 1 members separately...
[2021-10-29 17:22:52] Done.
Validation 17, 5 remaining
[2021-10-29 17:22:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:53] Number of windows considered: 1...
[2021-10-29 17:22:53] Bias-correcting 1 members separately...
[2021-10-29 17:22:53] Done.
Validation 18, 4 remaining
[2021-10-29 17:22:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:54] Number of windows considered: 1...
[2021-10-29 17:22:54] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:22:54] Done.
Validation 19, 3 remaining
[2021-10-29 17:22:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:56] Number of windows considered: 1...
[2021-10-29 17:22:56] Bias-correcting 1 members separately...
[2021-10-29 17:22:56] Done.
Validation 20, 2 remaining
[2021-10-29 17:22:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:57] Number of windows considered: 1...
[2021-10-29 17:22:57] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:22:57] Done.
Validation 21, 1 remaining
[2021-10-29 17:22:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:58] Number of windows considered: 1...
[2021-10-29 17:22:58] Bias-correcting 1 members separately...
[2021-10-29 17:22:58] Done.
Validation 22, 0 remaining
[2021-10-29 17:22:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:22:59] Number of windows considered: 1...
[2021-10-29 17:22:59] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:22:59] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 17:23:00] Performing annual aggregation...
[2021-10-29 17:23:00] Done.
[2021-10-29 17:23:00] - Computing climatology...
[2021-10-29 17:23:00] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:23:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:01] Number of windows considered: 1...
[2021-10-29 17:23:01] Bias-correcting 1 members separately...
[2021-10-29 17:23:01] Done.
Validation 2, 20 remaining
[2021-10-29 17:23:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:02] Number of windows considered: 1...
[2021-10-29 17:23:02] Bias-correcting 1 members separately...
[2021-10-29 17:23:02] Done.
Validation 3, 19 remaining
[2021-10-29 17:23:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:03] Number of windows considered: 1...
[2021-10-29 17:23:03] Bias-correcting 1 members separately...
[2021-10-29 17:23:04] Done.
Validation 4, 18 remaining
[2021-10-29 17:23:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:05] Number of windows considered: 1...
[2021-10-29 17:23:05] Bias-correcting 1 members separately...
[2021-10-29 17:23:05] Done.
Validation 5, 17 remaining
[2021-10-29 17:23:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:06] Number of windows considered: 1...
[2021-10-29 17:23:06] Bias-correcting 1 members separately...
[2021-10-29 17:23:06] Done.
Validation 6, 16 remaining
[2021-10-29 17:23:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:07] Number of windows considered: 1...
[2021-10-29 17:23:07] Bias-correcting 1 members separately...
[2021-10-29 17:23:07] Done.
Validation 7, 15 remaining
[2021-10-29 17:23:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:08] Number of windows considered: 1...
[2021-10-29 17:23:08] Bias-correcting 1 members separately...
[2021-10-29 17:23:08] Done.
Validation 8, 14 remaining
[2021-10-29 17:23:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:09] Number of windows considered: 1...
[2021-10-29 17:23:09] Bias-correcting 1 members separately...
[2021-10-29 17:23:09] Done.
Validation 9, 13 remaining
[2021-10-29 17:23:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:10] Number of windows considered: 1...
[2021-10-29 17:23:10] Bias-correcting 1 members separately...
[2021-10-29 17:23:10] Done.
Validation 10, 12 remaining
[2021-10-29 17:23:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:11] Number of windows considered: 1...
[2021-10-29 17:23:11] Bias-correcting 1 members separately...
[2021-10-29 17:23:11] Done.
Validation 11, 11 remaining
[2021-10-29 17:23:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:12] Number of windows considered: 1...
[2021-10-29 17:23:12] Bias-correcting 1 members separately...
[2021-10-29 17:23:13] Done.
Validation 12, 10 remaining
[2021-10-29 17:23:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:14] Number of windows considered: 1...
[2021-10-29 17:23:14] Bias-correcting 1 members separately...
[2021-10-29 17:23:14] Done.
Validation 13, 9 remaining
[2021-10-29 17:23:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:15] Number of windows considered: 1...
[2021-10-29 17:23:15] Bias-correcting 1 members separately...
[2021-10-29 17:23:15] Done.
Validation 14, 8 remaining
[2021-10-29 17:23:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:16] Number of windows considered: 1...
[2021-10-29 17:23:16] Bias-correcting 1 members separately...
[2021-10-29 17:23:16] Done.
Validation 15, 7 remaining
[2021-10-29 17:23:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:17] Number of windows considered: 1...
[2021-10-29 17:23:17] Bias-correcting 1 members separately...
[2021-10-29 17:23:17] Done.
Validation 16, 6 remaining
[2021-10-29 17:23:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:18] Number of windows considered: 1...
[2021-10-29 17:23:18] Bias-correcting 1 members separately...
[2021-10-29 17:23:18] Done.
Validation 17, 5 remaining
[2021-10-29 17:23:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:19] Number of windows considered: 1...
[2021-10-29 17:23:19] Bias-correcting 1 members separately...
[2021-10-29 17:23:19] Done.
Validation 18, 4 remaining
[2021-10-29 17:23:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:20] Number of windows considered: 1...
[2021-10-29 17:23:20] Bias-correcting 1 members separately...
[2021-10-29 17:23:20] Done.
Validation 19, 3 remaining
[2021-10-29 17:23:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:21] Number of windows considered: 1...
[2021-10-29 17:23:21] Bias-correcting 1 members separately...
[2021-10-29 17:23:21] Done.
Validation 20, 2 remaining
[2021-10-29 17:23:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:23] Number of windows considered: 1...
[2021-10-29 17:23:23] Bias-correcting 1 members separately...
[2021-10-29 17:23:23] Done.
Validation 21, 1 remaining
[2021-10-29 17:23:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:24] Number of windows considered: 1...
[2021-10-29 17:23:24] Bias-correcting 1 members separately...
[2021-10-29 17:23:24] Done.
Validation 22, 0 remaining
[2021-10-29 17:23:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:25] Number of windows considered: 1...
[2021-10-29 17:23:25] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:23:25] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 17:23:26] Performing annual aggregation...
[2021-10-29 17:23:26] Done.
[2021-10-29 17:23:26] - Computing climatology...
[2021-10-29 17:23:26] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm2.cl5 <- index.cal.station.cl5
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
GPQM2-WT5 PQM-WT5 EQM-WT5 GPQM-WT5
0.6545793 0.5123729 0.4747960 0.3358997
scores.st5.wt5 <- scores
Complete period (WO WTs)
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
[2021-10-29 17:23:26] Performing annual aggregation...
no non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Inf[2021-10-29 17:23:26] Done.
[2021-10-29 17:23:26] - Computing climatology...
[2021-10-29 17:23:26] - Done.
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)
index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
[2021-10-29 17:23:26] Performing annual aggregation...
[2021-10-29 17:23:26] Done.
[2021-10-29 17:23:26] - Computing climatology...
[2021-10-29 17:23:26] - Done.
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "pqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-10-29 17:23:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:28] Number of windows considered: 1...
[2021-10-29 17:23:28] Bias-correcting 1 members separately...
[2021-10-29 17:23:28] Done.
Validation 2, 20 remaining
[2021-10-29 17:23:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:29] Number of windows considered: 1...
[2021-10-29 17:23:29] Bias-correcting 1 members separately...
[2021-10-29 17:23:29] Done.
Validation 3, 19 remaining
[2021-10-29 17:23:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:30] Number of windows considered: 1...
[2021-10-29 17:23:30] Bias-correcting 1 members separately...
[2021-10-29 17:23:30] Done.
Validation 4, 18 remaining
[2021-10-29 17:23:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:31] Number of windows considered: 1...
[2021-10-29 17:23:31] Bias-correcting 1 members separately...
[2021-10-29 17:23:31] Done.
Validation 5, 17 remaining
[2021-10-29 17:23:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:32] Number of windows considered: 1...
[2021-10-29 17:23:32] Bias-correcting 1 members separately...
[2021-10-29 17:23:32] Done.
Validation 6, 16 remaining
[2021-10-29 17:23:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:33] Number of windows considered: 1...
[2021-10-29 17:23:33] Bias-correcting 1 members separately...
[2021-10-29 17:23:33] Done.
Validation 7, 15 remaining
[2021-10-29 17:23:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:34] Number of windows considered: 1...
[2021-10-29 17:23:34] Bias-correcting 1 members separately...
[2021-10-29 17:23:34] Done.
Validation 8, 14 remaining
[2021-10-29 17:23:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:35] Number of windows considered: 1...
[2021-10-29 17:23:35] Bias-correcting 1 members separately...
[2021-10-29 17:23:35] Done.
Validation 9, 13 remaining
[2021-10-29 17:23:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:36] Number of windows considered: 1...
[2021-10-29 17:23:36] Bias-correcting 1 members separately...
[2021-10-29 17:23:36] Done.
Validation 10, 12 remaining
[2021-10-29 17:23:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:37] Number of windows considered: 1...
[2021-10-29 17:23:37] Bias-correcting 1 members separately...
[2021-10-29 17:23:38] Done.
Validation 11, 11 remaining
[2021-10-29 17:23:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:39] Number of windows considered: 1...
[2021-10-29 17:23:39] Bias-correcting 1 members separately...
[2021-10-29 17:23:39] Done.
Validation 12, 10 remaining
[2021-10-29 17:23:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:40] Number of windows considered: 1...
[2021-10-29 17:23:40] Bias-correcting 1 members separately...
[2021-10-29 17:23:40] Done.
Validation 13, 9 remaining
[2021-10-29 17:23:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:41] Number of windows considered: 1...
[2021-10-29 17:23:41] Bias-correcting 1 members separately...
[2021-10-29 17:23:41] Done.
Validation 14, 8 remaining
[2021-10-29 17:23:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:42] Number of windows considered: 1...
[2021-10-29 17:23:42] Bias-correcting 1 members separately...
[2021-10-29 17:23:42] Done.
Validation 15, 7 remaining
[2021-10-29 17:23:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:43] Number of windows considered: 1...
[2021-10-29 17:23:43] Bias-correcting 1 members separately...
[2021-10-29 17:23:43] Done.
Validation 16, 6 remaining
[2021-10-29 17:23:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:44] Number of windows considered: 1...
[2021-10-29 17:23:44] Bias-correcting 1 members separately...
[2021-10-29 17:23:44] Done.
Validation 17, 5 remaining
[2021-10-29 17:23:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:46] Number of windows considered: 1...
[2021-10-29 17:23:46] Bias-correcting 1 members separately...
[2021-10-29 17:23:46] Done.
Validation 18, 4 remaining
[2021-10-29 17:23:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:47] Number of windows considered: 1...
[2021-10-29 17:23:47] Bias-correcting 1 members separately...
[2021-10-29 17:23:47] Done.
Validation 19, 3 remaining
[2021-10-29 17:23:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:48] Number of windows considered: 1...
[2021-10-29 17:23:48] Bias-correcting 1 members separately...
[2021-10-29 17:23:48] Done.
Validation 20, 2 remaining
[2021-10-29 17:23:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:49] Number of windows considered: 1...
[2021-10-29 17:23:49] Bias-correcting 1 members separately...
[2021-10-29 17:23:49] Done.
Validation 21, 1 remaining
[2021-10-29 17:23:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:49] Number of windows considered: 1...
[2021-10-29 17:23:49] Bias-correcting 1 members separately...
[2021-10-29 17:23:50] Done.
Validation 22, 0 remaining
[2021-10-29 17:23:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:50] Number of windows considered: 1...
[2021-10-29 17:23:50] Bias-correcting 1 members separately...
[2021-10-29 17:23:51] Done.
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:23:51] Performing annual aggregation...
[2021-10-29 17:23:51] Done.
[2021-10-29 17:23:51] - Computing climatology...
[2021-10-29 17:23:51] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.pqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "eqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-10-29 17:23:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:52] Number of windows considered: 1...
[2021-10-29 17:23:52] Bias-correcting 1 members separately...
[2021-10-29 17:23:52] Done.
Validation 2, 20 remaining
[2021-10-29 17:23:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:53] Number of windows considered: 1...
[2021-10-29 17:23:53] Bias-correcting 1 members separately...
[2021-10-29 17:23:53] Done.
Validation 3, 19 remaining
[2021-10-29 17:23:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:54] Number of windows considered: 1...
[2021-10-29 17:23:54] Bias-correcting 1 members separately...
[2021-10-29 17:23:54] Done.
Validation 4, 18 remaining
[2021-10-29 17:23:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:55] Number of windows considered: 1...
[2021-10-29 17:23:55] Bias-correcting 1 members separately...
[2021-10-29 17:23:55] Done.
Validation 5, 17 remaining
[2021-10-29 17:23:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:56] Number of windows considered: 1...
[2021-10-29 17:23:56] Bias-correcting 1 members separately...
[2021-10-29 17:23:56] Done.
Validation 6, 16 remaining
[2021-10-29 17:23:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:57] Number of windows considered: 1...
[2021-10-29 17:23:57] Bias-correcting 1 members separately...
[2021-10-29 17:23:58] Done.
Validation 7, 15 remaining
[2021-10-29 17:23:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:58] Number of windows considered: 1...
[2021-10-29 17:23:58] Bias-correcting 1 members separately...
[2021-10-29 17:23:58] Done.
Validation 8, 14 remaining
[2021-10-29 17:23:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:23:59] Number of windows considered: 1...
[2021-10-29 17:23:59] Bias-correcting 1 members separately...
[2021-10-29 17:24:00] Done.
Validation 9, 13 remaining
[2021-10-29 17:24:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:01] Number of windows considered: 1...
[2021-10-29 17:24:01] Bias-correcting 1 members separately...
[2021-10-29 17:24:01] Done.
Validation 10, 12 remaining
[2021-10-29 17:24:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:02] Number of windows considered: 1...
[2021-10-29 17:24:02] Bias-correcting 1 members separately...
[2021-10-29 17:24:02] Done.
Validation 11, 11 remaining
[2021-10-29 17:24:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:03] Number of windows considered: 1...
[2021-10-29 17:24:03] Bias-correcting 1 members separately...
[2021-10-29 17:24:03] Done.
Validation 12, 10 remaining
[2021-10-29 17:24:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:04] Number of windows considered: 1...
[2021-10-29 17:24:04] Bias-correcting 1 members separately...
[2021-10-29 17:24:04] Done.
Validation 13, 9 remaining
[2021-10-29 17:24:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:05] Number of windows considered: 1...
[2021-10-29 17:24:05] Bias-correcting 1 members separately...
[2021-10-29 17:24:05] Done.
Validation 14, 8 remaining
[2021-10-29 17:24:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:06] Number of windows considered: 1...
[2021-10-29 17:24:06] Bias-correcting 1 members separately...
[2021-10-29 17:24:06] Done.
Validation 15, 7 remaining
[2021-10-29 17:24:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:07] Number of windows considered: 1...
[2021-10-29 17:24:07] Bias-correcting 1 members separately...
[2021-10-29 17:24:07] Done.
Validation 16, 6 remaining
[2021-10-29 17:24:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:08] Number of windows considered: 1...
[2021-10-29 17:24:08] Bias-correcting 1 members separately...
[2021-10-29 17:24:08] Done.
Validation 17, 5 remaining
[2021-10-29 17:24:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:09] Number of windows considered: 1...
[2021-10-29 17:24:09] Bias-correcting 1 members separately...
[2021-10-29 17:24:09] Done.
Validation 18, 4 remaining
[2021-10-29 17:24:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:11] Number of windows considered: 1...
[2021-10-29 17:24:11] Bias-correcting 1 members separately...
[2021-10-29 17:24:11] Done.
Validation 19, 3 remaining
[2021-10-29 17:24:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:12] Number of windows considered: 1...
[2021-10-29 17:24:12] Bias-correcting 1 members separately...
[2021-10-29 17:24:12] Done.
Validation 20, 2 remaining
[2021-10-29 17:24:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:13] Number of windows considered: 1...
[2021-10-29 17:24:13] Bias-correcting 1 members separately...
[2021-10-29 17:24:13] Done.
Validation 21, 1 remaining
[2021-10-29 17:24:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:14] Number of windows considered: 1...
[2021-10-29 17:24:14] Bias-correcting 1 members separately...
[2021-10-29 17:24:14] Done.
Validation 22, 0 remaining
[2021-10-29 17:24:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:15] Number of windows considered: 1...
[2021-10-29 17:24:15] Bias-correcting 1 members separately...
[2021-10-29 17:24:15] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:24:16] Performing annual aggregation...
[2021-10-29 17:24:16] Done.
[2021-10-29 17:24:16] - Computing climatology...
[2021-10-29 17:24:16] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.eqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", cross.val = "loo")
Validation 1, 21 remaining
[2021-10-29 17:24:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:17] Number of windows considered: 1...
[2021-10-29 17:24:17] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:17] Done.
Validation 2, 20 remaining
[2021-10-29 17:24:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:18] Number of windows considered: 1...
[2021-10-29 17:24:18] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:19] Done.
Validation 3, 19 remaining
[2021-10-29 17:24:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:20] Number of windows considered: 1...
[2021-10-29 17:24:20] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:20] Done.
Validation 4, 18 remaining
[2021-10-29 17:24:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:21] Number of windows considered: 1...
[2021-10-29 17:24:21] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:21] Done.
Validation 5, 17 remaining
[2021-10-29 17:24:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:22] Number of windows considered: 1...
[2021-10-29 17:24:23] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:23] Done.
Validation 6, 16 remaining
[2021-10-29 17:24:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:24] Number of windows considered: 1...
[2021-10-29 17:24:24] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:24:24] Done.
Validation 7, 15 remaining
[2021-10-29 17:24:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:25] Number of windows considered: 1...
[2021-10-29 17:24:25] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:26] Done.
Validation 8, 14 remaining
[2021-10-29 17:24:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:27] Number of windows considered: 1...
[2021-10-29 17:24:27] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:27] Done.
Validation 9, 13 remaining
[2021-10-29 17:24:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:28] Number of windows considered: 1...
[2021-10-29 17:24:28] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:28] Done.
Validation 10, 12 remaining
[2021-10-29 17:24:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:29] Number of windows considered: 1...
[2021-10-29 17:24:29] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:29] Done.
Validation 11, 11 remaining
[2021-10-29 17:24:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:31] Number of windows considered: 1...
[2021-10-29 17:24:31] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:31] Done.
Validation 12, 10 remaining
[2021-10-29 17:24:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:32] Number of windows considered: 1...
[2021-10-29 17:24:32] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:32] Done.
Validation 13, 9 remaining
[2021-10-29 17:24:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:33] Number of windows considered: 1...
[2021-10-29 17:24:33] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:34] Done.
Validation 14, 8 remaining
[2021-10-29 17:24:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:35] Number of windows considered: 1...
[2021-10-29 17:24:35] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:35] Done.
Validation 15, 7 remaining
[2021-10-29 17:24:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:36] Number of windows considered: 1...
[2021-10-29 17:24:36] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:36] Done.
Validation 16, 6 remaining
[2021-10-29 17:24:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:37] Number of windows considered: 1...
[2021-10-29 17:24:37] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:38] Done.
Validation 17, 5 remaining
[2021-10-29 17:24:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:39] Number of windows considered: 1...
[2021-10-29 17:24:39] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:24:39] Done.
Validation 18, 4 remaining
[2021-10-29 17:24:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:40] Number of windows considered: 1...
[2021-10-29 17:24:40] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:41] Done.
Validation 19, 3 remaining
[2021-10-29 17:24:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:42] Number of windows considered: 1...
[2021-10-29 17:24:42] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:24:42] Done.
Validation 20, 2 remaining
[2021-10-29 17:24:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:43] Number of windows considered: 1...
[2021-10-29 17:24:43] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:43] Done.
Validation 21, 1 remaining
[2021-10-29 17:24:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:45] Number of windows considered: 1...
[2021-10-29 17:24:45] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:24:45] Done.
Validation 22, 0 remaining
[2021-10-29 17:24:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:46] Number of windows considered: 1...
[2021-10-29 17:24:46] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:46] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:24:47] Performing annual aggregation...
[2021-10-29 17:24:47] Done.
[2021-10-29 17:24:47] - Computing climatology...
[2021-10-29 17:24:47] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", theta = .7, cross.val = "loo")
Validation 1, 21 remaining
[2021-10-29 17:24:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:48] Number of windows considered: 1...
[2021-10-29 17:24:48] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:48] Done.
Validation 2, 20 remaining
[2021-10-29 17:24:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:50] Number of windows considered: 1...
[2021-10-29 17:24:50] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:50] Done.
Validation 3, 19 remaining
[2021-10-29 17:24:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:51] Number of windows considered: 1...
[2021-10-29 17:24:51] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:51] Done.
Validation 4, 18 remaining
[2021-10-29 17:24:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:52] Number of windows considered: 1...
[2021-10-29 17:24:52] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:52] Done.
Validation 5, 17 remaining
[2021-10-29 17:24:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:54] Number of windows considered: 1...
[2021-10-29 17:24:54] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:54] Done.
Validation 6, 16 remaining
[2021-10-29 17:24:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:55] Number of windows considered: 1...
[2021-10-29 17:24:55] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:24:55] Done.
Validation 7, 15 remaining
[2021-10-29 17:24:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:56] Number of windows considered: 1...
[2021-10-29 17:24:56] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:56] Done.
Validation 8, 14 remaining
[2021-10-29 17:24:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:57] Number of windows considered: 1...
[2021-10-29 17:24:57] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:58] Done.
Validation 9, 13 remaining
[2021-10-29 17:24:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:24:59] Number of windows considered: 1...
[2021-10-29 17:24:59] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:24:59] Done.
Validation 10, 12 remaining
[2021-10-29 17:25:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:00] Number of windows considered: 1...
[2021-10-29 17:25:00] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:25:00] Done.
Validation 11, 11 remaining
[2021-10-29 17:25:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:01] Number of windows considered: 1...
[2021-10-29 17:25:01] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:25:02] Done.
Validation 12, 10 remaining
[2021-10-29 17:25:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:03] Number of windows considered: 1...
[2021-10-29 17:25:03] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:25:03] Done.
Validation 13, 9 remaining
[2021-10-29 17:25:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:04] Number of windows considered: 1...
[2021-10-29 17:25:04] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:25:04] Done.
Validation 14, 8 remaining
[2021-10-29 17:25:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:06] Number of windows considered: 1...
[2021-10-29 17:25:06] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:25:06] Done.
Validation 15, 7 remaining
[2021-10-29 17:25:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:07] Number of windows considered: 1...
[2021-10-29 17:25:07] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:25:07] Done.
Validation 16, 6 remaining
[2021-10-29 17:25:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:08] Number of windows considered: 1...
[2021-10-29 17:25:08] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:25:08] Done.
Validation 17, 5 remaining
[2021-10-29 17:25:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:10] Number of windows considered: 1...
[2021-10-29 17:25:10] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:25:10] Done.
Validation 18, 4 remaining
[2021-10-29 17:25:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:11] Number of windows considered: 1...
[2021-10-29 17:25:11] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:25:11] Done.
Validation 19, 3 remaining
[2021-10-29 17:25:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:12] Number of windows considered: 1...
[2021-10-29 17:25:12] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:25:12] Done.
Validation 20, 2 remaining
[2021-10-29 17:25:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:13] Number of windows considered: 1...
[2021-10-29 17:25:13] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:25:14] Done.
Validation 21, 1 remaining
[2021-10-29 17:25:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:15] Number of windows considered: 1...
[2021-10-29 17:25:15] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:25:15] Done.
Validation 22, 0 remaining
[2021-10-29 17:25:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:16] Number of windows considered: 1...
[2021-10-29 17:25:16] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:25:16] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:25:17] Performing annual aggregation...
[2021-10-29 17:25:17] Done.
[2021-10-29 17:25:17] - Computing climatology...
[2021-10-29 17:25:17] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm2.complete <- index.cal.station.complete
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.trmm.complete[i]-index.obs.complete[i]),abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
score.trmm <- c()
for (i in c(1:9)) {
score.trmm <- c(score.trmm, norm.vector[[i]][1])
}
score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][2])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][3])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][4])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][5])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
EQM-C GPQM2-C TRMM PQM-C GPQM-C
0.7411586 0.6953732 0.6480341 0.6210702 0.2169236
scores.complete <- scores
paste(names(scores.st5.wt1[1]),names(scores.st5.wt2[1]),names(scores.st5.wt3[1]),names(scores.st5.wt4[1]),names(scores.st5.wt5[1]), names(scores.complete[1]))
[1] "EQM-WT1 EQM-WT2 GPQM2-WT3 PQM-WT4 GPQM2-WT5 EQM-C"
Combination of techniques by WT
cal.station.cl1.eqm <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "eqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 17:25:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:19] Number of windows considered: 1...
[2021-10-29 17:25:19] Bias-correcting 1 members separately...
[2021-10-29 17:25:19] Done.
Validation 2, 20 remaining
[2021-10-29 17:25:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:20] Number of windows considered: 1...
[2021-10-29 17:25:20] Bias-correcting 1 members separately...
[2021-10-29 17:25:20] Done.
Validation 3, 19 remaining
[2021-10-29 17:25:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:21] Number of windows considered: 1...
[2021-10-29 17:25:21] Bias-correcting 1 members separately...
[2021-10-29 17:25:21] Done.
Validation 4, 18 remaining
[2021-10-29 17:25:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:23] Number of windows considered: 1...
[2021-10-29 17:25:23] Bias-correcting 1 members separately...
[2021-10-29 17:25:23] Done.
Validation 5, 17 remaining
[2021-10-29 17:25:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:24] Number of windows considered: 1...
[2021-10-29 17:25:24] Bias-correcting 1 members separately...
[2021-10-29 17:25:24] Done.
Validation 6, 16 remaining
[2021-10-29 17:25:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:25] Number of windows considered: 1...
[2021-10-29 17:25:25] Bias-correcting 1 members separately...
[2021-10-29 17:25:25] Done.
Validation 7, 15 remaining
[2021-10-29 17:25:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:27] Number of windows considered: 1...
[2021-10-29 17:25:27] Bias-correcting 1 members separately...
[2021-10-29 17:25:27] Done.
Validation 8, 14 remaining
[2021-10-29 17:25:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:28] Number of windows considered: 1...
[2021-10-29 17:25:28] Bias-correcting 1 members separately...
[2021-10-29 17:25:28] Done.
Validation 9, 13 remaining
[2021-10-29 17:25:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:29] Number of windows considered: 1...
[2021-10-29 17:25:29] Bias-correcting 1 members separately...
[2021-10-29 17:25:29] Done.
Validation 10, 12 remaining
[2021-10-29 17:25:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:31] Number of windows considered: 1...
[2021-10-29 17:25:31] Bias-correcting 1 members separately...
[2021-10-29 17:25:31] Done.
Validation 11, 11 remaining
[2021-10-29 17:25:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:32] Number of windows considered: 1...
[2021-10-29 17:25:32] Bias-correcting 1 members separately...
[2021-10-29 17:25:33] Done.
Validation 12, 10 remaining
[2021-10-29 17:25:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:34] Number of windows considered: 1...
[2021-10-29 17:25:34] Bias-correcting 1 members separately...
[2021-10-29 17:25:34] Done.
Validation 13, 9 remaining
[2021-10-29 17:25:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:35] Number of windows considered: 1...
[2021-10-29 17:25:35] Bias-correcting 1 members separately...
[2021-10-29 17:25:35] Done.
Validation 14, 8 remaining
[2021-10-29 17:25:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:36] Number of windows considered: 1...
[2021-10-29 17:25:36] Bias-correcting 1 members separately...
[2021-10-29 17:25:36] Done.
Validation 15, 7 remaining
[2021-10-29 17:25:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:37] Number of windows considered: 1...
[2021-10-29 17:25:37] Bias-correcting 1 members separately...
[2021-10-29 17:25:37] Done.
Validation 16, 6 remaining
[2021-10-29 17:25:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:38] Number of windows considered: 1...
[2021-10-29 17:25:38] Bias-correcting 1 members separately...
[2021-10-29 17:25:38] Done.
Validation 17, 5 remaining
[2021-10-29 17:25:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:39] Number of windows considered: 1...
[2021-10-29 17:25:39] Bias-correcting 1 members separately...
[2021-10-29 17:25:39] Done.
Validation 18, 4 remaining
[2021-10-29 17:25:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:40] Number of windows considered: 1...
[2021-10-29 17:25:40] Bias-correcting 1 members separately...
[2021-10-29 17:25:40] Done.
Validation 19, 3 remaining
[2021-10-29 17:25:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:41] Number of windows considered: 1...
[2021-10-29 17:25:41] Bias-correcting 1 members separately...
[2021-10-29 17:25:41] Done.
Validation 20, 2 remaining
[2021-10-29 17:25:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:42] Number of windows considered: 1...
[2021-10-29 17:25:42] Bias-correcting 1 members separately...
[2021-10-29 17:25:42] Done.
Validation 21, 1 remaining
[2021-10-29 17:25:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:43] Number of windows considered: 1...
[2021-10-29 17:25:43] Bias-correcting 1 members separately...
[2021-10-29 17:25:43] Done.
Validation 22, 0 remaining
[2021-10-29 17:25:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:44] Number of windows considered: 1...
[2021-10-29 17:25:44] Bias-correcting 1 members separately...
[2021-10-29 17:25:44] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl1.eqm$Dates$start <- as.POSIXct(cal.station.cl1.eqm$Dates$start,tz = "GMT")
cal.station.cl1.eqm$Dates$end <- as.POSIXct(cal.station.cl1.eqm$Dates$end,tz = "GMT")
cal.station.cl2.eqm <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "eqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 17:25:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:46] Number of windows considered: 1...
[2021-10-29 17:25:46] Bias-correcting 1 members separately...
[2021-10-29 17:25:46] Done.
Validation 2, 20 remaining
[2021-10-29 17:25:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:47] Number of windows considered: 1...
[2021-10-29 17:25:47] Bias-correcting 1 members separately...
[2021-10-29 17:25:47] Done.
Validation 3, 19 remaining
[2021-10-29 17:25:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:48] Number of windows considered: 1...
[2021-10-29 17:25:48] Bias-correcting 1 members separately...
[2021-10-29 17:25:48] Done.
Validation 4, 18 remaining
[2021-10-29 17:25:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:49] Number of windows considered: 1...
[2021-10-29 17:25:49] Bias-correcting 1 members separately...
[2021-10-29 17:25:49] Done.
Validation 5, 17 remaining
[2021-10-29 17:25:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:50] Number of windows considered: 1...
[2021-10-29 17:25:50] Bias-correcting 1 members separately...
[2021-10-29 17:25:50] Done.
Validation 6, 16 remaining
[2021-10-29 17:25:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:51] Number of windows considered: 1...
[2021-10-29 17:25:51] Bias-correcting 1 members separately...
[2021-10-29 17:25:51] Done.
Validation 7, 15 remaining
[2021-10-29 17:25:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:52] Number of windows considered: 1...
[2021-10-29 17:25:52] Bias-correcting 1 members separately...
[2021-10-29 17:25:53] Done.
Validation 8, 14 remaining
[2021-10-29 17:25:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:54] Number of windows considered: 1...
[2021-10-29 17:25:54] Bias-correcting 1 members separately...
[2021-10-29 17:25:54] Done.
Validation 9, 13 remaining
[2021-10-29 17:25:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:55] Number of windows considered: 1...
[2021-10-29 17:25:55] Bias-correcting 1 members separately...
[2021-10-29 17:25:55] Done.
Validation 10, 12 remaining
[2021-10-29 17:25:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:56] Number of windows considered: 1...
[2021-10-29 17:25:56] Bias-correcting 1 members separately...
[2021-10-29 17:25:56] Done.
Validation 11, 11 remaining
[2021-10-29 17:25:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:57] Number of windows considered: 1...
[2021-10-29 17:25:57] Bias-correcting 1 members separately...
[2021-10-29 17:25:57] Done.
Validation 12, 10 remaining
[2021-10-29 17:25:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:58] Number of windows considered: 1...
[2021-10-29 17:25:58] Bias-correcting 1 members separately...
[2021-10-29 17:25:58] Done.
Validation 13, 9 remaining
[2021-10-29 17:25:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:25:59] Number of windows considered: 1...
[2021-10-29 17:25:59] Bias-correcting 1 members separately...
[2021-10-29 17:25:59] Done.
Validation 14, 8 remaining
[2021-10-29 17:26:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:00] Number of windows considered: 1...
[2021-10-29 17:26:00] Bias-correcting 1 members separately...
[2021-10-29 17:26:01] Done.
Validation 15, 7 remaining
[2021-10-29 17:26:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:02] Number of windows considered: 1...
[2021-10-29 17:26:02] Bias-correcting 1 members separately...
[2021-10-29 17:26:02] Done.
Validation 16, 6 remaining
[2021-10-29 17:26:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:03] Number of windows considered: 1...
[2021-10-29 17:26:03] Bias-correcting 1 members separately...
[2021-10-29 17:26:03] Done.
Validation 17, 5 remaining
[2021-10-29 17:26:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:04] Number of windows considered: 1...
[2021-10-29 17:26:04] Bias-correcting 1 members separately...
[2021-10-29 17:26:04] Done.
Validation 18, 4 remaining
[2021-10-29 17:26:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:05] Number of windows considered: 1...
[2021-10-29 17:26:05] Bias-correcting 1 members separately...
[2021-10-29 17:26:05] Done.
Validation 19, 3 remaining
[2021-10-29 17:26:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:06] Number of windows considered: 1...
[2021-10-29 17:26:06] Bias-correcting 1 members separately...
[2021-10-29 17:26:07] Done.
Validation 20, 2 remaining
[2021-10-29 17:26:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:08] Number of windows considered: 1...
[2021-10-29 17:26:08] Bias-correcting 1 members separately...
[2021-10-29 17:26:08] Done.
Validation 21, 1 remaining
[2021-10-29 17:26:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:09] Number of windows considered: 1...
[2021-10-29 17:26:09] Bias-correcting 1 members separately...
[2021-10-29 17:26:09] Done.
Validation 22, 0 remaining
[2021-10-29 17:26:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:10] Number of windows considered: 1...
[2021-10-29 17:26:10] Bias-correcting 1 members separately...
[2021-10-29 17:26:10] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl2.eqm$Dates$start <- as.POSIXct(cal.station.cl2.eqm$Dates$start,tz = "GMT")
cal.station.cl2.eqm$Dates$end <- as.POSIXct(cal.station.cl2.eqm$Dates$end,tz = "GMT")
cal.station.cl3.gpqm2 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm", theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:26:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:12] Number of windows considered: 1...
[2021-10-29 17:26:12] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:12] Done.
Validation 2, 20 remaining
[2021-10-29 17:26:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:13] Number of windows considered: 1...
[2021-10-29 17:26:13] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:13] Done.
Validation 3, 19 remaining
[2021-10-29 17:26:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:14] Number of windows considered: 1...
[2021-10-29 17:26:14] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:15] Done.
Validation 4, 18 remaining
[2021-10-29 17:26:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:16] Number of windows considered: 1...
[2021-10-29 17:26:16] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:16] Done.
Validation 5, 17 remaining
[2021-10-29 17:26:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:17] Number of windows considered: 1...
[2021-10-29 17:26:17] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:17] Done.
Validation 6, 16 remaining
[2021-10-29 17:26:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:18] Number of windows considered: 1...
[2021-10-29 17:26:18] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:18] Done.
Validation 7, 15 remaining
[2021-10-29 17:26:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:19] Number of windows considered: 1...
[2021-10-29 17:26:19] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:19] Done.
Validation 8, 14 remaining
[2021-10-29 17:26:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:20] Number of windows considered: 1...
[2021-10-29 17:26:20] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:20] Done.
Validation 9, 13 remaining
[2021-10-29 17:26:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:21] Number of windows considered: 1...
[2021-10-29 17:26:21] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:22] Done.
Validation 10, 12 remaining
[2021-10-29 17:26:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:23] Number of windows considered: 1...
[2021-10-29 17:26:23] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:23] Done.
Validation 11, 11 remaining
[2021-10-29 17:26:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:24] Number of windows considered: 1...
[2021-10-29 17:26:24] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:24] Done.
Validation 12, 10 remaining
[2021-10-29 17:26:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:25] Number of windows considered: 1...
[2021-10-29 17:26:25] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:25] Done.
Validation 13, 9 remaining
[2021-10-29 17:26:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:26] Number of windows considered: 1...
[2021-10-29 17:26:26] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:27] Done.
Validation 14, 8 remaining
[2021-10-29 17:26:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:28] Number of windows considered: 1...
[2021-10-29 17:26:28] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:28] Done.
Validation 15, 7 remaining
[2021-10-29 17:26:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:29] Number of windows considered: 1...
[2021-10-29 17:26:29] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:29] Done.
Validation 16, 6 remaining
[2021-10-29 17:26:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:30] Number of windows considered: 1...
[2021-10-29 17:26:30] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:30] Done.
Validation 17, 5 remaining
[2021-10-29 17:26:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:31] Number of windows considered: 1...
[2021-10-29 17:26:31] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:31] Done.
Validation 18, 4 remaining
[2021-10-29 17:26:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:32] Number of windows considered: 1...
[2021-10-29 17:26:32] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:33] Done.
Validation 19, 3 remaining
[2021-10-29 17:26:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:34] Number of windows considered: 1...
[2021-10-29 17:26:34] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:34] Done.
Validation 20, 2 remaining
[2021-10-29 17:26:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:35] Number of windows considered: 1...
[2021-10-29 17:26:35] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:35] Done.
Validation 21, 1 remaining
[2021-10-29 17:26:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:36] Number of windows considered: 1...
[2021-10-29 17:26:36] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:36] Done.
Validation 22, 0 remaining
[2021-10-29 17:26:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:37] Number of windows considered: 1...
[2021-10-29 17:26:37] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:26:37] Done.
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl3.gpqm2$Dates$start <- as.POSIXct(cal.station.cl3.gpqm2$Dates$start,tz = "GMT")
cal.station.cl3.gpqm2$Dates$end <- as.POSIXct(cal.station.cl3.gpqm2$Dates$end,tz = "GMT")
cal.station.cl4.pqm <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "pqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 17:26:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:39] Number of windows considered: 1...
[2021-10-29 17:26:39] Bias-correcting 1 members separately...
[2021-10-29 17:26:39] Done.
Validation 2, 20 remaining
[2021-10-29 17:26:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:40] Number of windows considered: 1...
[2021-10-29 17:26:40] Bias-correcting 1 members separately...
[2021-10-29 17:26:40] Done.
Validation 3, 19 remaining
[2021-10-29 17:26:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:41] Number of windows considered: 1...
[2021-10-29 17:26:41] Bias-correcting 1 members separately...
[2021-10-29 17:26:41] Done.
Validation 4, 18 remaining
[2021-10-29 17:26:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:43] Number of windows considered: 1...
[2021-10-29 17:26:43] Bias-correcting 1 members separately...
[2021-10-29 17:26:43] Done.
Validation 5, 17 remaining
[2021-10-29 17:26:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:44] Number of windows considered: 1...
[2021-10-29 17:26:44] Bias-correcting 1 members separately...
[2021-10-29 17:26:44] Done.
Validation 6, 16 remaining
[2021-10-29 17:26:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:45] Number of windows considered: 1...
[2021-10-29 17:26:45] Bias-correcting 1 members separately...
[2021-10-29 17:26:45] Done.
Validation 7, 15 remaining
[2021-10-29 17:26:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:46] Number of windows considered: 1...
[2021-10-29 17:26:46] Bias-correcting 1 members separately...
[2021-10-29 17:26:47] Done.
Validation 8, 14 remaining
[2021-10-29 17:26:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:48] Number of windows considered: 1...
[2021-10-29 17:26:48] Bias-correcting 1 members separately...
[2021-10-29 17:26:48] Done.
Validation 9, 13 remaining
[2021-10-29 17:26:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:49] Number of windows considered: 1...
[2021-10-29 17:26:49] Bias-correcting 1 members separately...
[2021-10-29 17:26:49] Done.
Validation 10, 12 remaining
[2021-10-29 17:26:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:51] Number of windows considered: 1...
[2021-10-29 17:26:51] Bias-correcting 1 members separately...
[2021-10-29 17:26:51] Done.
Validation 11, 11 remaining
[2021-10-29 17:26:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:52] Number of windows considered: 1...
[2021-10-29 17:26:52] Bias-correcting 1 members separately...
[2021-10-29 17:26:52] Done.
Validation 12, 10 remaining
[2021-10-29 17:26:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:53] Number of windows considered: 1...
[2021-10-29 17:26:53] Bias-correcting 1 members separately...
[2021-10-29 17:26:53] Done.
Validation 13, 9 remaining
[2021-10-29 17:26:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:54] Number of windows considered: 1...
[2021-10-29 17:26:54] Bias-correcting 1 members separately...
[2021-10-29 17:26:54] Done.
Validation 14, 8 remaining
[2021-10-29 17:26:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:56] Number of windows considered: 1...
[2021-10-29 17:26:56] Bias-correcting 1 members separately...
[2021-10-29 17:26:56] Done.
Validation 15, 7 remaining
[2021-10-29 17:26:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:57] Number of windows considered: 1...
[2021-10-29 17:26:57] Bias-correcting 1 members separately...
[2021-10-29 17:26:57] Done.
Validation 16, 6 remaining
[2021-10-29 17:26:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:58] Number of windows considered: 1...
[2021-10-29 17:26:58] Bias-correcting 1 members separately...
[2021-10-29 17:26:58] Done.
Validation 17, 5 remaining
[2021-10-29 17:26:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:26:59] Number of windows considered: 1...
[2021-10-29 17:26:59] Bias-correcting 1 members separately...
[2021-10-29 17:26:59] Done.
Validation 18, 4 remaining
[2021-10-29 17:27:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:01] Number of windows considered: 1...
[2021-10-29 17:27:01] Bias-correcting 1 members separately...
[2021-10-29 17:27:01] Done.
Validation 19, 3 remaining
[2021-10-29 17:27:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:02] Number of windows considered: 1...
[2021-10-29 17:27:02] Bias-correcting 1 members separately...
[2021-10-29 17:27:02] Done.
Validation 20, 2 remaining
[2021-10-29 17:27:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:03] Number of windows considered: 1...
[2021-10-29 17:27:03] Bias-correcting 1 members separately...
[2021-10-29 17:27:03] Done.
Validation 21, 1 remaining
[2021-10-29 17:27:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:04] Number of windows considered: 1...
[2021-10-29 17:27:04] Bias-correcting 1 members separately...
[2021-10-29 17:27:04] Done.
Validation 22, 0 remaining
[2021-10-29 17:27:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:05] Number of windows considered: 1...
[2021-10-29 17:27:05] Bias-correcting 1 members separately...
[2021-10-29 17:27:05] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl4.pqm$Dates$start <- as.POSIXct(cal.station.cl4.pqm$Dates$start,tz = "GMT")
cal.station.cl4.pqm$Dates$end <- as.POSIXct(cal.station.cl4.pqm$Dates$end,tz = "GMT")
cal.station.cl5.gpqm2 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm",theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:27:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:08] Number of windows considered: 1...
[2021-10-29 17:27:08] Bias-correcting 1 members separately...
[2021-10-29 17:27:08] Done.
Validation 2, 20 remaining
[2021-10-29 17:27:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:09] Number of windows considered: 1...
[2021-10-29 17:27:09] Bias-correcting 1 members separately...
[2021-10-29 17:27:09] Done.
Validation 3, 19 remaining
[2021-10-29 17:27:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:10] Number of windows considered: 1...
[2021-10-29 17:27:10] Bias-correcting 1 members separately...
[2021-10-29 17:27:10] Done.
Validation 4, 18 remaining
[2021-10-29 17:27:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:12] Number of windows considered: 1...
[2021-10-29 17:27:12] Bias-correcting 1 members separately...
[2021-10-29 17:27:12] Done.
Validation 5, 17 remaining
[2021-10-29 17:27:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:13] Number of windows considered: 1...
[2021-10-29 17:27:13] Bias-correcting 1 members separately...
[2021-10-29 17:27:13] Done.
Validation 6, 16 remaining
[2021-10-29 17:27:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:14] Number of windows considered: 1...
[2021-10-29 17:27:14] Bias-correcting 1 members separately...
[2021-10-29 17:27:14] Done.
Validation 7, 15 remaining
[2021-10-29 17:27:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:15] Number of windows considered: 1...
[2021-10-29 17:27:15] Bias-correcting 1 members separately...
[2021-10-29 17:27:15] Done.
Validation 8, 14 remaining
[2021-10-29 17:27:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:16] Number of windows considered: 1...
[2021-10-29 17:27:16] Bias-correcting 1 members separately...
[2021-10-29 17:27:16] Done.
Validation 9, 13 remaining
[2021-10-29 17:27:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:17] Number of windows considered: 1...
[2021-10-29 17:27:17] Bias-correcting 1 members separately...
[2021-10-29 17:27:17] Done.
Validation 10, 12 remaining
[2021-10-29 17:27:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:18] Number of windows considered: 1...
[2021-10-29 17:27:18] Bias-correcting 1 members separately...
[2021-10-29 17:27:18] Done.
Validation 11, 11 remaining
[2021-10-29 17:27:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:19] Number of windows considered: 1...
[2021-10-29 17:27:19] Bias-correcting 1 members separately...
[2021-10-29 17:27:19] Done.
Validation 12, 10 remaining
[2021-10-29 17:27:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:20] Number of windows considered: 1...
[2021-10-29 17:27:20] Bias-correcting 1 members separately...
[2021-10-29 17:27:20] Done.
Validation 13, 9 remaining
[2021-10-29 17:27:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:21] Number of windows considered: 1...
[2021-10-29 17:27:21] Bias-correcting 1 members separately...
[2021-10-29 17:27:21] Done.
Validation 14, 8 remaining
[2021-10-29 17:27:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:22] Number of windows considered: 1...
[2021-10-29 17:27:22] Bias-correcting 1 members separately...
[2021-10-29 17:27:22] Done.
Validation 15, 7 remaining
[2021-10-29 17:27:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:23] Number of windows considered: 1...
[2021-10-29 17:27:23] Bias-correcting 1 members separately...
[2021-10-29 17:27:23] Done.
Validation 16, 6 remaining
[2021-10-29 17:27:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:24] Number of windows considered: 1...
[2021-10-29 17:27:24] Bias-correcting 1 members separately...
[2021-10-29 17:27:24] Done.
Validation 17, 5 remaining
[2021-10-29 17:27:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:25] Number of windows considered: 1...
[2021-10-29 17:27:25] Bias-correcting 1 members separately...
[2021-10-29 17:27:25] Done.
Validation 18, 4 remaining
[2021-10-29 17:27:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:26] Number of windows considered: 1...
[2021-10-29 17:27:26] Bias-correcting 1 members separately...
[2021-10-29 17:27:26] Done.
Validation 19, 3 remaining
[2021-10-29 17:27:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:27] Number of windows considered: 1...
[2021-10-29 17:27:27] Bias-correcting 1 members separately...
[2021-10-29 17:27:27] Done.
Validation 20, 2 remaining
[2021-10-29 17:27:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:28] Number of windows considered: 1...
[2021-10-29 17:27:28] Bias-correcting 1 members separately...
[2021-10-29 17:27:28] Done.
Validation 21, 1 remaining
[2021-10-29 17:27:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:29] Number of windows considered: 1...
[2021-10-29 17:27:29] Bias-correcting 1 members separately...
[2021-10-29 17:27:29] Done.
Validation 22, 0 remaining
[2021-10-29 17:27:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:30] Number of windows considered: 1...
[2021-10-29 17:27:30] Bias-correcting 1 members separately...
NaNs produced[2021-10-29 17:27:30] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl5.gpqm2$Dates$start <- as.POSIXct(cal.station.cl5.gpqm2$Dates$start,tz = "GMT")
cal.station.cl5.gpqm2$Dates$end <- as.POSIXct(cal.station.cl5.gpqm2$Dates$end,tz = "GMT")
idx <- which(!is.na(cal.station.cl1.eqm$Data))
cal.station.cl1.eqm <- subsetDimension(cal.station.cl1.eqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl2.eqm$Data))
cal.station.cl2.eqm <- subsetDimension(cal.station.cl2.eqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl3.gpqm2$Data))
cal.station.cl3.gpqm2 <- subsetDimension(cal.station.cl3.gpqm2, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl4.pqm$Data))
cal.station.cl4.pqm <- subsetDimension(cal.station.cl4.pqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl5.gpqm2$Data))
cal.station.cl5.gpqm2 <- subsetDimension(cal.station.cl5.gpqm2, dimension = "time", indices = idx)
wt_conditioned <- bindGrid(cal.station.cl1.eqm, cal.station.cl2.eqm, cal.station.cl3.gpqm2,
cal.station.cl4.pqm, cal.station.cl5.gpqm2, dimension = "time")
attr(wt_conditioned$Data, "dimensions") <- "time"
#cambiar de tipo de biasCorrection y fillGridDates
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "eqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-10-29 17:27:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:33] Number of windows considered: 1...
[2021-10-29 17:27:33] Bias-correcting 1 members separately...
[2021-10-29 17:27:33] Done.
Validation 2, 20 remaining
[2021-10-29 17:27:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:34] Number of windows considered: 1...
[2021-10-29 17:27:34] Bias-correcting 1 members separately...
[2021-10-29 17:27:34] Done.
Validation 3, 19 remaining
[2021-10-29 17:27:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:35] Number of windows considered: 1...
[2021-10-29 17:27:35] Bias-correcting 1 members separately...
[2021-10-29 17:27:35] Done.
Validation 4, 18 remaining
[2021-10-29 17:27:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:36] Number of windows considered: 1...
[2021-10-29 17:27:36] Bias-correcting 1 members separately...
[2021-10-29 17:27:36] Done.
Validation 5, 17 remaining
[2021-10-29 17:27:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:37] Number of windows considered: 1...
[2021-10-29 17:27:37] Bias-correcting 1 members separately...
[2021-10-29 17:27:37] Done.
Validation 6, 16 remaining
[2021-10-29 17:27:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:38] Number of windows considered: 1...
[2021-10-29 17:27:38] Bias-correcting 1 members separately...
[2021-10-29 17:27:38] Done.
Validation 7, 15 remaining
[2021-10-29 17:27:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:39] Number of windows considered: 1...
[2021-10-29 17:27:39] Bias-correcting 1 members separately...
[2021-10-29 17:27:39] Done.
Validation 8, 14 remaining
[2021-10-29 17:27:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:41] Number of windows considered: 1...
[2021-10-29 17:27:41] Bias-correcting 1 members separately...
[2021-10-29 17:27:41] Done.
Validation 9, 13 remaining
[2021-10-29 17:27:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:42] Number of windows considered: 1...
[2021-10-29 17:27:42] Bias-correcting 1 members separately...
[2021-10-29 17:27:42] Done.
Validation 10, 12 remaining
[2021-10-29 17:27:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:43] Number of windows considered: 1...
[2021-10-29 17:27:43] Bias-correcting 1 members separately...
[2021-10-29 17:27:43] Done.
Validation 11, 11 remaining
[2021-10-29 17:27:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:44] Number of windows considered: 1...
[2021-10-29 17:27:44] Bias-correcting 1 members separately...
[2021-10-29 17:27:44] Done.
Validation 12, 10 remaining
[2021-10-29 17:27:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:45] Number of windows considered: 1...
[2021-10-29 17:27:45] Bias-correcting 1 members separately...
[2021-10-29 17:27:45] Done.
Validation 13, 9 remaining
[2021-10-29 17:27:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:46] Number of windows considered: 1...
[2021-10-29 17:27:46] Bias-correcting 1 members separately...
[2021-10-29 17:27:47] Done.
Validation 14, 8 remaining
[2021-10-29 17:27:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:48] Number of windows considered: 1...
[2021-10-29 17:27:48] Bias-correcting 1 members separately...
[2021-10-29 17:27:48] Done.
Validation 15, 7 remaining
[2021-10-29 17:27:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:49] Number of windows considered: 1...
[2021-10-29 17:27:49] Bias-correcting 1 members separately...
[2021-10-29 17:27:49] Done.
Validation 16, 6 remaining
[2021-10-29 17:27:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:50] Number of windows considered: 1...
[2021-10-29 17:27:50] Bias-correcting 1 members separately...
[2021-10-29 17:27:50] Done.
Validation 17, 5 remaining
[2021-10-29 17:27:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:51] Number of windows considered: 1...
[2021-10-29 17:27:51] Bias-correcting 1 members separately...
[2021-10-29 17:27:51] Done.
Validation 18, 4 remaining
[2021-10-29 17:27:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:52] Number of windows considered: 1...
[2021-10-29 17:27:52] Bias-correcting 1 members separately...
[2021-10-29 17:27:52] Done.
Validation 19, 3 remaining
[2021-10-29 17:27:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:53] Number of windows considered: 1...
[2021-10-29 17:27:53] Bias-correcting 1 members separately...
[2021-10-29 17:27:53] Done.
Validation 20, 2 remaining
[2021-10-29 17:27:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:54] Number of windows considered: 1...
[2021-10-29 17:27:54] Bias-correcting 1 members separately...
[2021-10-29 17:27:54] Done.
Validation 21, 1 remaining
[2021-10-29 17:27:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:56] Number of windows considered: 1...
[2021-10-29 17:27:56] Bias-correcting 1 members separately...
[2021-10-29 17:27:56] Done.
Validation 22, 0 remaining
[2021-10-29 17:27:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:27:57] Number of windows considered: 1...
[2021-10-29 17:27:57] Bias-correcting 1 members separately...
[2021-10-29 17:27:57] Done.
# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))
index.combinated.rv20max <- MaxReturnValue(wt_conditioned)
[2021-10-29 17:27:57] Performing annual aggregation...
[2021-10-29 17:27:57] Done.
[2021-10-29 17:27:57] - Computing climatology...
[2021-10-29 17:27:57] - Done.
index.combinated <- c(index.combinated, index.combinated.rv20max)
index.eqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.eqm <- c(index.eqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.eqm.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:27:58] Performing annual aggregation...
[2021-10-29 17:27:58] Done.
[2021-10-29 17:27:58] - Computing climatology...
[2021-10-29 17:27:58] - Done.
index.eqm<- c(index.eqm ,index.eqm.rv20max)
index.eqm
Skewness SDII R10 R10p R20 R20p P98Wet
6.127724e+00 1.595982e+01 1.738860e-01 4.233521e+04 9.671397e-02 3.365643e+04 7.980479e+01
P98WetAmount RV20_max
8.217302e+03 2.381686e+02
diff.conditioned <- abs(index.obs-index.combinated)
diff.eqm <- abs(index.obs-index.eqm)
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
score.combinated <- c()
for (i in c(1:9)) {
score.combinated <- c(score.combinated, norm.vector[[i]][5])
}
score.combinated <- mean(score.combinated)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
Combined EQM-C GPQM2-C PQM-C GPQM-C
0.8244949 0.6971774 0.6630859 0.5759513 0.1493637
df <- data.frame(index.obs, index.combinated, index.eqm)
colnames(df) <- c("Observation","Conditioned", "EQM")
format(df, digits = 3, scientific = 5)
bias.df <- data.frame(diff.conditioned, diff.eqm)
colnames(bias.df) <- c("Bias Conditioned", "Bias EQM")
format(bias.df, digits = 3, scientific = 5)
df.st1 <- df
bias.df.st1 <- bias.df
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100
names(bias.rel.cond) <- names(diff.conditioned)
bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100
names(bias.rel.no.cond) <- names(diff.conditioned)
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)
colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias EQM")
format(bias.rel.df, digits = 3, scientific = 5)
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))
abline(a = 0, b = 1)
station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))
points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))
idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))
station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)
points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)
legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))
grid()

Aoloau, American Samoa
i=6
station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
[2021-10-29 17:28:01] Performing annual aggregation...
[2021-10-29 17:28:01] Done.
[2021-10-29 17:28:01] - Computing climatology...
[2021-10-29 17:28:01] - Done.
index.obs <- c(index.obs, index.obs.rv20max)
index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
[2021-10-29 17:28:01] Performing annual aggregation...
[2021-10-29 17:28:01] Done.
[2021-10-29 17:28:01] - Computing climatology...
[2021-10-29 17:28:01] - Done.
index.trmm <- c(index.trmm, index.trmm.rv20max)
WT1
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))
station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
[2021-10-29 17:28:01] Performing annual aggregation...
no non-missing arguments to max; returning -Inf[2021-10-29 17:28:01] Done.
[2021-10-29 17:28:01] - Computing climatology...
[2021-10-29 17:28:01] - Done.
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)
index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
[2021-10-29 17:28:01] Performing annual aggregation...
[2021-10-29 17:28:01] Done.
[2021-10-29 17:28:01] - Computing climatology...
[2021-10-29 17:28:01] - Done.
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")
station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "pqm",cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:28:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:02] Number of windows considered: 1...
[2021-10-29 17:28:02] Bias-correcting 1 members separately...
[2021-10-29 17:28:02] Done.
Validation 2, 20 remaining
[2021-10-29 17:28:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:03] Number of windows considered: 1...
[2021-10-29 17:28:03] Bias-correcting 1 members separately...
[2021-10-29 17:28:03] Done.
Validation 3, 19 remaining
[2021-10-29 17:28:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:04] Number of windows considered: 1...
[2021-10-29 17:28:04] Bias-correcting 1 members separately...
[2021-10-29 17:28:04] Done.
Validation 4, 18 remaining
[2021-10-29 17:28:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:05] Number of windows considered: 1...
[2021-10-29 17:28:05] Bias-correcting 1 members separately...
[2021-10-29 17:28:05] Done.
Validation 5, 17 remaining
[2021-10-29 17:28:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:06] Number of windows considered: 1...
[2021-10-29 17:28:06] Bias-correcting 1 members separately...
[2021-10-29 17:28:06] Done.
Validation 6, 16 remaining
[2021-10-29 17:28:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:08] Number of windows considered: 1...
[2021-10-29 17:28:08] Bias-correcting 1 members separately...
[2021-10-29 17:28:08] Done.
Validation 7, 15 remaining
[2021-10-29 17:28:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:09] Number of windows considered: 1...
[2021-10-29 17:28:09] Bias-correcting 1 members separately...
[2021-10-29 17:28:09] Done.
Validation 8, 14 remaining
[2021-10-29 17:28:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:10] Number of windows considered: 1...
[2021-10-29 17:28:10] Bias-correcting 1 members separately...
[2021-10-29 17:28:10] Done.
Validation 9, 13 remaining
[2021-10-29 17:28:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:11] Number of windows considered: 1...
[2021-10-29 17:28:11] Bias-correcting 1 members separately...
[2021-10-29 17:28:11] Done.
Validation 10, 12 remaining
[2021-10-29 17:28:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:12] Number of windows considered: 1...
[2021-10-29 17:28:12] Bias-correcting 1 members separately...
[2021-10-29 17:28:12] Done.
Validation 11, 11 remaining
[2021-10-29 17:28:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:13] Number of windows considered: 1...
[2021-10-29 17:28:13] Bias-correcting 1 members separately...
[2021-10-29 17:28:13] Done.
Validation 12, 10 remaining
[2021-10-29 17:28:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:15] Number of windows considered: 1...
[2021-10-29 17:28:15] Bias-correcting 1 members separately...
[2021-10-29 17:28:15] Done.
Validation 13, 9 remaining
[2021-10-29 17:28:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:16] Number of windows considered: 1...
[2021-10-29 17:28:16] Bias-correcting 1 members separately...
[2021-10-29 17:28:16] Done.
Validation 14, 8 remaining
[2021-10-29 17:28:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:17] Number of windows considered: 1...
[2021-10-29 17:28:17] Bias-correcting 1 members separately...
[2021-10-29 17:28:17] Done.
Validation 15, 7 remaining
[2021-10-29 17:28:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:18] Number of windows considered: 1...
[2021-10-29 17:28:18] Bias-correcting 1 members separately...
[2021-10-29 17:28:18] Done.
Validation 16, 6 remaining
[2021-10-29 17:28:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:19] Number of windows considered: 1...
[2021-10-29 17:28:19] Bias-correcting 1 members separately...
[2021-10-29 17:28:19] Done.
Validation 17, 5 remaining
[2021-10-29 17:28:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:20] Number of windows considered: 1...
[2021-10-29 17:28:20] Bias-correcting 1 members separately...
[2021-10-29 17:28:20] Done.
Validation 18, 4 remaining
[2021-10-29 17:28:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:21] Number of windows considered: 1...
[2021-10-29 17:28:21] Bias-correcting 1 members separately...
[2021-10-29 17:28:21] Done.
Validation 19, 3 remaining
[2021-10-29 17:28:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:23] Number of windows considered: 1...
[2021-10-29 17:28:23] Bias-correcting 1 members separately...
[2021-10-29 17:28:23] Done.
Validation 20, 2 remaining
[2021-10-29 17:28:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:24] Number of windows considered: 1...
[2021-10-29 17:28:24] Bias-correcting 1 members separately...
[2021-10-29 17:28:24] Done.
Validation 21, 1 remaining
[2021-10-29 17:28:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:25] Number of windows considered: 1...
[2021-10-29 17:28:25] Bias-correcting 1 members separately...
[2021-10-29 17:28:25] Done.
Validation 22, 0 remaining
[2021-10-29 17:28:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:26] Number of windows considered: 1...
[2021-10-29 17:28:26] Bias-correcting 1 members separately...
[2021-10-29 17:28:26] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 17:28:27] Performing annual aggregation...
[2021-10-29 17:28:27] Done.
[2021-10-29 17:28:27] - Computing climatology...
[2021-10-29 17:28:27] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.pqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:28:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:28] Number of windows considered: 1...
[2021-10-29 17:28:28] Bias-correcting 1 members separately...
[2021-10-29 17:28:28] Done.
Validation 2, 20 remaining
[2021-10-29 17:28:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:29] Number of windows considered: 1...
[2021-10-29 17:28:29] Bias-correcting 1 members separately...
[2021-10-29 17:28:30] Done.
Validation 3, 19 remaining
[2021-10-29 17:28:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:31] Number of windows considered: 1...
[2021-10-29 17:28:31] Bias-correcting 1 members separately...
[2021-10-29 17:28:31] Done.
Validation 4, 18 remaining
[2021-10-29 17:28:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:32] Number of windows considered: 1...
[2021-10-29 17:28:32] Bias-correcting 1 members separately...
[2021-10-29 17:28:32] Done.
Validation 5, 17 remaining
[2021-10-29 17:28:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:33] Number of windows considered: 1...
[2021-10-29 17:28:33] Bias-correcting 1 members separately...
[2021-10-29 17:28:34] Done.
Validation 6, 16 remaining
[2021-10-29 17:28:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:35] Number of windows considered: 1...
[2021-10-29 17:28:35] Bias-correcting 1 members separately...
[2021-10-29 17:28:35] Done.
Validation 7, 15 remaining
[2021-10-29 17:28:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:36] Number of windows considered: 1...
[2021-10-29 17:28:36] Bias-correcting 1 members separately...
[2021-10-29 17:28:36] Done.
Validation 8, 14 remaining
[2021-10-29 17:28:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:37] Number of windows considered: 1...
[2021-10-29 17:28:37] Bias-correcting 1 members separately...
[2021-10-29 17:28:37] Done.
Validation 9, 13 remaining
[2021-10-29 17:28:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:39] Number of windows considered: 1...
[2021-10-29 17:28:39] Bias-correcting 1 members separately...
[2021-10-29 17:28:39] Done.
Validation 10, 12 remaining
[2021-10-29 17:28:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:40] Number of windows considered: 1...
[2021-10-29 17:28:40] Bias-correcting 1 members separately...
[2021-10-29 17:28:40] Done.
Validation 11, 11 remaining
[2021-10-29 17:28:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:41] Number of windows considered: 1...
[2021-10-29 17:28:41] Bias-correcting 1 members separately...
[2021-10-29 17:28:41] Done.
Validation 12, 10 remaining
[2021-10-29 17:28:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:43] Number of windows considered: 1...
[2021-10-29 17:28:43] Bias-correcting 1 members separately...
[2021-10-29 17:28:43] Done.
Validation 13, 9 remaining
[2021-10-29 17:28:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:44] Number of windows considered: 1...
[2021-10-29 17:28:44] Bias-correcting 1 members separately...
[2021-10-29 17:28:44] Done.
Validation 14, 8 remaining
[2021-10-29 17:28:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:45] Number of windows considered: 1...
[2021-10-29 17:28:45] Bias-correcting 1 members separately...
[2021-10-29 17:28:45] Done.
Validation 15, 7 remaining
[2021-10-29 17:28:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:47] Number of windows considered: 1...
[2021-10-29 17:28:47] Bias-correcting 1 members separately...
[2021-10-29 17:28:47] Done.
Validation 16, 6 remaining
[2021-10-29 17:28:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:48] Number of windows considered: 1...
[2021-10-29 17:28:48] Bias-correcting 1 members separately...
[2021-10-29 17:28:48] Done.
Validation 17, 5 remaining
[2021-10-29 17:28:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:49] Number of windows considered: 1...
[2021-10-29 17:28:49] Bias-correcting 1 members separately...
[2021-10-29 17:28:49] Done.
Validation 18, 4 remaining
[2021-10-29 17:28:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:50] Number of windows considered: 1...
[2021-10-29 17:28:50] Bias-correcting 1 members separately...
[2021-10-29 17:28:51] Done.
Validation 19, 3 remaining
[2021-10-29 17:28:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:52] Number of windows considered: 1...
[2021-10-29 17:28:52] Bias-correcting 1 members separately...
[2021-10-29 17:28:52] Done.
Validation 20, 2 remaining
[2021-10-29 17:28:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:53] Number of windows considered: 1...
[2021-10-29 17:28:53] Bias-correcting 1 members separately...
[2021-10-29 17:28:53] Done.
Validation 21, 1 remaining
[2021-10-29 17:28:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:54] Number of windows considered: 1...
[2021-10-29 17:28:54] Bias-correcting 1 members separately...
[2021-10-29 17:28:55] Done.
Validation 22, 0 remaining
[2021-10-29 17:28:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:56] Number of windows considered: 1...
[2021-10-29 17:28:56] Bias-correcting 1 members separately...
[2021-10-29 17:28:56] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 17:28:57] Performing annual aggregation...
[2021-10-29 17:28:57] Done.
[2021-10-29 17:28:57] - Computing climatology...
[2021-10-29 17:28:57] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.eqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:28:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:58] Number of windows considered: 1...
[2021-10-29 17:28:58] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:28:58] Done.
Validation 2, 20 remaining
[2021-10-29 17:28:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:28:59] Number of windows considered: 1...
[2021-10-29 17:28:59] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:28:59] Done.
Validation 3, 19 remaining
[2021-10-29 17:29:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:00] Number of windows considered: 1...
[2021-10-29 17:29:00] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:00] Done.
Validation 4, 18 remaining
[2021-10-29 17:29:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:01] Number of windows considered: 1...
[2021-10-29 17:29:01] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:29:01] Done.
Validation 5, 17 remaining
[2021-10-29 17:29:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:02] Number of windows considered: 1...
[2021-10-29 17:29:02] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:29:02] Done.
Validation 6, 16 remaining
[2021-10-29 17:29:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:03] Number of windows considered: 1...
[2021-10-29 17:29:03] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:29:03] Done.
Validation 7, 15 remaining
[2021-10-29 17:29:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:04] Number of windows considered: 1...
[2021-10-29 17:29:04] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:29:04] Done.
Validation 8, 14 remaining
[2021-10-29 17:29:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:05] Number of windows considered: 1...
[2021-10-29 17:29:05] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:06] Done.
Validation 9, 13 remaining
[2021-10-29 17:29:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:06] Number of windows considered: 1...
[2021-10-29 17:29:06] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:07] Done.
Validation 10, 12 remaining
[2021-10-29 17:29:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:07] Number of windows considered: 1...
[2021-10-29 17:29:07] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:08] Done.
Validation 11, 11 remaining
[2021-10-29 17:29:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:09] Number of windows considered: 1...
[2021-10-29 17:29:09] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:29:09] Done.
Validation 12, 10 remaining
[2021-10-29 17:29:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:10] Number of windows considered: 1...
[2021-10-29 17:29:10] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:10] Done.
Validation 13, 9 remaining
[2021-10-29 17:29:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:11] Number of windows considered: 1...
[2021-10-29 17:29:11] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:29:11] Done.
Validation 14, 8 remaining
[2021-10-29 17:29:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:12] Number of windows considered: 1...
[2021-10-29 17:29:12] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:29:12] Done.
Validation 15, 7 remaining
[2021-10-29 17:29:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:13] Number of windows considered: 1...
[2021-10-29 17:29:13] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:29:13] Done.
Validation 16, 6 remaining
[2021-10-29 17:29:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:14] Number of windows considered: 1...
[2021-10-29 17:29:14] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:29:14] Done.
Validation 17, 5 remaining
[2021-10-29 17:29:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:15] Number of windows considered: 1...
[2021-10-29 17:29:15] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:29:15] Done.
Validation 18, 4 remaining
[2021-10-29 17:29:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:16] Number of windows considered: 1...
[2021-10-29 17:29:16] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:29:17] Done.
Validation 19, 3 remaining
[2021-10-29 17:29:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:17] Number of windows considered: 1...
[2021-10-29 17:29:17] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:29:18] Done.
Validation 20, 2 remaining
[2021-10-29 17:29:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:19] Number of windows considered: 1...
[2021-10-29 17:29:19] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:29:19] Done.
Validation 21, 1 remaining
[2021-10-29 17:29:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:20] Number of windows considered: 1...
[2021-10-29 17:29:20] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:29:20] Done.
Validation 22, 0 remaining
[2021-10-29 17:29:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:21] Number of windows considered: 1...
[2021-10-29 17:29:21] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:29:21] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 17:29:22] Performing annual aggregation...
[2021-10-29 17:29:22] Done.
[2021-10-29 17:29:22] - Computing climatology...
[2021-10-29 17:29:22] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:29:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:23] Number of windows considered: 1...
[2021-10-29 17:29:23] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:23] Done.
Validation 2, 20 remaining
[2021-10-29 17:29:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:24] Number of windows considered: 1...
[2021-10-29 17:29:24] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:24] Done.
Validation 3, 19 remaining
[2021-10-29 17:29:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:25] Number of windows considered: 1...
[2021-10-29 17:29:25] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:25] Done.
Validation 4, 18 remaining
[2021-10-29 17:29:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:26] Number of windows considered: 1...
[2021-10-29 17:29:26] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:27] Done.
Validation 5, 17 remaining
[2021-10-29 17:29:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:28] Number of windows considered: 1...
[2021-10-29 17:29:28] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:28] Done.
Validation 6, 16 remaining
[2021-10-29 17:29:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:29] Number of windows considered: 1...
[2021-10-29 17:29:29] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:29] Done.
Validation 7, 15 remaining
[2021-10-29 17:29:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:30] Number of windows considered: 1...
[2021-10-29 17:29:30] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:30] Done.
Validation 8, 14 remaining
[2021-10-29 17:29:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:31] Number of windows considered: 1...
[2021-10-29 17:29:31] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:31] Done.
Validation 9, 13 remaining
[2021-10-29 17:29:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:32] Number of windows considered: 1...
[2021-10-29 17:29:32] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:32] Done.
Validation 10, 12 remaining
[2021-10-29 17:29:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:33] Number of windows considered: 1...
[2021-10-29 17:29:33] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:33] Done.
Validation 11, 11 remaining
[2021-10-29 17:29:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:34] Number of windows considered: 1...
[2021-10-29 17:29:34] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:35] Done.
Validation 12, 10 remaining
[2021-10-29 17:29:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:36] Number of windows considered: 1...
[2021-10-29 17:29:36] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:36] Done.
Validation 13, 9 remaining
[2021-10-29 17:29:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:37] Number of windows considered: 1...
[2021-10-29 17:29:37] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:37] Done.
Validation 14, 8 remaining
[2021-10-29 17:29:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:38] Number of windows considered: 1...
[2021-10-29 17:29:38] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:38] Done.
Validation 15, 7 remaining
[2021-10-29 17:29:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:39] Number of windows considered: 1...
[2021-10-29 17:29:39] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:39] Done.
Validation 16, 6 remaining
[2021-10-29 17:29:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:40] Number of windows considered: 1...
[2021-10-29 17:29:40] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:40] Done.
Validation 17, 5 remaining
[2021-10-29 17:29:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:41] Number of windows considered: 1...
[2021-10-29 17:29:41] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:42] Done.
Validation 18, 4 remaining
[2021-10-29 17:29:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:43] Number of windows considered: 1...
[2021-10-29 17:29:43] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:43] Done.
Validation 19, 3 remaining
[2021-10-29 17:29:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:44] Number of windows considered: 1...
[2021-10-29 17:29:44] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:44] Done.
Validation 20, 2 remaining
[2021-10-29 17:29:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:45] Number of windows considered: 1...
[2021-10-29 17:29:45] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:45] Done.
Validation 21, 1 remaining
[2021-10-29 17:29:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:46] Number of windows considered: 1...
[2021-10-29 17:29:46] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:46] Done.
Validation 22, 0 remaining
[2021-10-29 17:29:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:47] Number of windows considered: 1...
[2021-10-29 17:29:47] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:29:47] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-10-29 17:29:48] Performing annual aggregation...
[2021-10-29 17:29:48] Done.
[2021-10-29 17:29:48] - Computing climatology...
[2021-10-29 17:29:48] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm2.cl1 <- index.cal.station.cl1
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i]))
}
normalization <- function(measure){
measure.norm <- c()
#measure must be a vector with the value of a certain measure of different calibrations
for (i in c(1:length(measure))) {
measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
}
return(measure.norm)
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
scores.st6.wt1 <- scores
WT2
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))
station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
[2021-10-29 17:29:49] Performing annual aggregation...
no non-missing arguments to max; returning -Inf[2021-10-29 17:29:49] Done.
[2021-10-29 17:29:49] - Computing climatology...
[2021-10-29 17:29:49] - Done.
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)
index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
[2021-10-29 17:29:49] Performing annual aggregation...
[2021-10-29 17:29:49] Done.
[2021-10-29 17:29:49] - Computing climatology...
[2021-10-29 17:29:49] - Done.
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")
station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:29:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:50] Number of windows considered: 1...
[2021-10-29 17:29:50] Bias-correcting 1 members separately...
[2021-10-29 17:29:50] Done.
Validation 2, 20 remaining
[2021-10-29 17:29:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:51] Number of windows considered: 1...
[2021-10-29 17:29:51] Bias-correcting 1 members separately...
[2021-10-29 17:29:51] Done.
Validation 3, 19 remaining
[2021-10-29 17:29:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:52] Number of windows considered: 1...
[2021-10-29 17:29:52] Bias-correcting 1 members separately...
[2021-10-29 17:29:52] Done.
Validation 4, 18 remaining
[2021-10-29 17:29:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:53] Number of windows considered: 1...
[2021-10-29 17:29:53] Bias-correcting 1 members separately...
[2021-10-29 17:29:53] Done.
Validation 5, 17 remaining
[2021-10-29 17:29:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:54] Number of windows considered: 1...
[2021-10-29 17:29:54] Bias-correcting 1 members separately...
[2021-10-29 17:29:55] Done.
Validation 6, 16 remaining
[2021-10-29 17:29:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:56] Number of windows considered: 1...
[2021-10-29 17:29:56] Bias-correcting 1 members separately...
[2021-10-29 17:29:56] Done.
Validation 7, 15 remaining
[2021-10-29 17:29:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:57] Number of windows considered: 1...
[2021-10-29 17:29:57] Bias-correcting 1 members separately...
[2021-10-29 17:29:57] Done.
Validation 8, 14 remaining
[2021-10-29 17:29:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:58] Number of windows considered: 1...
[2021-10-29 17:29:58] Bias-correcting 1 members separately...
[2021-10-29 17:29:58] Done.
Validation 9, 13 remaining
[2021-10-29 17:29:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:29:59] Number of windows considered: 1...
[2021-10-29 17:29:59] Bias-correcting 1 members separately...
[2021-10-29 17:29:59] Done.
Validation 10, 12 remaining
[2021-10-29 17:30:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:00] Number of windows considered: 1...
[2021-10-29 17:30:00] Bias-correcting 1 members separately...
[2021-10-29 17:30:00] Done.
Validation 11, 11 remaining
[2021-10-29 17:30:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:01] Number of windows considered: 1...
[2021-10-29 17:30:01] Bias-correcting 1 members separately...
[2021-10-29 17:30:01] Done.
Validation 12, 10 remaining
[2021-10-29 17:30:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:02] Number of windows considered: 1...
[2021-10-29 17:30:02] Bias-correcting 1 members separately...
[2021-10-29 17:30:02] Done.
Validation 13, 9 remaining
[2021-10-29 17:30:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:03] Number of windows considered: 1...
[2021-10-29 17:30:03] Bias-correcting 1 members separately...
[2021-10-29 17:30:03] Done.
Validation 14, 8 remaining
[2021-10-29 17:30:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:05] Number of windows considered: 1...
[2021-10-29 17:30:05] Bias-correcting 1 members separately...
[2021-10-29 17:30:05] Done.
Validation 15, 7 remaining
[2021-10-29 17:30:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:06] Number of windows considered: 1...
[2021-10-29 17:30:06] Bias-correcting 1 members separately...
[2021-10-29 17:30:06] Done.
Validation 16, 6 remaining
[2021-10-29 17:30:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:07] Number of windows considered: 1...
[2021-10-29 17:30:07] Bias-correcting 1 members separately...
[2021-10-29 17:30:07] Done.
Validation 17, 5 remaining
[2021-10-29 17:30:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:08] Number of windows considered: 1...
[2021-10-29 17:30:08] Bias-correcting 1 members separately...
[2021-10-29 17:30:08] Done.
Validation 18, 4 remaining
[2021-10-29 17:30:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:09] Number of windows considered: 1...
[2021-10-29 17:30:09] Bias-correcting 1 members separately...
[2021-10-29 17:30:09] Done.
Validation 19, 3 remaining
[2021-10-29 17:30:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:10] Number of windows considered: 1...
[2021-10-29 17:30:10] Bias-correcting 1 members separately...
[2021-10-29 17:30:10] Done.
Validation 20, 2 remaining
[2021-10-29 17:30:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:11] Number of windows considered: 1...
[2021-10-29 17:30:11] Bias-correcting 1 members separately...
[2021-10-29 17:30:12] Done.
Validation 21, 1 remaining
[2021-10-29 17:30:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:13] Number of windows considered: 1...
[2021-10-29 17:30:13] Bias-correcting 1 members separately...
[2021-10-29 17:30:13] Done.
Validation 22, 0 remaining
[2021-10-29 17:30:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:14] Number of windows considered: 1...
[2021-10-29 17:30:14] Bias-correcting 1 members separately...
[2021-10-29 17:30:14] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 17:30:15] Performing annual aggregation...
[2021-10-29 17:30:15] Done.
[2021-10-29 17:30:15] - Computing climatology...
[2021-10-29 17:30:15] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.pqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:30:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:16] Number of windows considered: 1...
[2021-10-29 17:30:16] Bias-correcting 1 members separately...
[2021-10-29 17:30:16] Done.
Validation 2, 20 remaining
[2021-10-29 17:30:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:17] Number of windows considered: 1...
[2021-10-29 17:30:17] Bias-correcting 1 members separately...
[2021-10-29 17:30:17] Done.
Validation 3, 19 remaining
[2021-10-29 17:30:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:19] Number of windows considered: 1...
[2021-10-29 17:30:19] Bias-correcting 1 members separately...
[2021-10-29 17:30:19] Done.
Validation 4, 18 remaining
[2021-10-29 17:30:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:20] Number of windows considered: 1...
[2021-10-29 17:30:20] Bias-correcting 1 members separately...
[2021-10-29 17:30:20] Done.
Validation 5, 17 remaining
[2021-10-29 17:30:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:21] Number of windows considered: 1...
[2021-10-29 17:30:21] Bias-correcting 1 members separately...
[2021-10-29 17:30:21] Done.
Validation 6, 16 remaining
[2021-10-29 17:30:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:23] Number of windows considered: 1...
[2021-10-29 17:30:23] Bias-correcting 1 members separately...
[2021-10-29 17:30:23] Done.
Validation 7, 15 remaining
[2021-10-29 17:30:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:24] Number of windows considered: 1...
[2021-10-29 17:30:24] Bias-correcting 1 members separately...
[2021-10-29 17:30:24] Done.
Validation 8, 14 remaining
[2021-10-29 17:30:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:25] Number of windows considered: 1...
[2021-10-29 17:30:25] Bias-correcting 1 members separately...
[2021-10-29 17:30:25] Done.
Validation 9, 13 remaining
[2021-10-29 17:30:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:27] Number of windows considered: 1...
[2021-10-29 17:30:27] Bias-correcting 1 members separately...
[2021-10-29 17:30:27] Done.
Validation 10, 12 remaining
[2021-10-29 17:30:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:28] Number of windows considered: 1...
[2021-10-29 17:30:28] Bias-correcting 1 members separately...
[2021-10-29 17:30:28] Done.
Validation 11, 11 remaining
[2021-10-29 17:30:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:29] Number of windows considered: 1...
[2021-10-29 17:30:29] Bias-correcting 1 members separately...
[2021-10-29 17:30:29] Done.
Validation 12, 10 remaining
[2021-10-29 17:30:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:30] Number of windows considered: 1...
[2021-10-29 17:30:30] Bias-correcting 1 members separately...
[2021-10-29 17:30:31] Done.
Validation 13, 9 remaining
[2021-10-29 17:30:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:32] Number of windows considered: 1...
[2021-10-29 17:30:32] Bias-correcting 1 members separately...
[2021-10-29 17:30:32] Done.
Validation 14, 8 remaining
[2021-10-29 17:30:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:33] Number of windows considered: 1...
[2021-10-29 17:30:33] Bias-correcting 1 members separately...
[2021-10-29 17:30:33] Done.
Validation 15, 7 remaining
[2021-10-29 17:30:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:35] Number of windows considered: 1...
[2021-10-29 17:30:35] Bias-correcting 1 members separately...
[2021-10-29 17:30:35] Done.
Validation 16, 6 remaining
[2021-10-29 17:30:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:36] Number of windows considered: 1...
[2021-10-29 17:30:36] Bias-correcting 1 members separately...
[2021-10-29 17:30:36] Done.
Validation 17, 5 remaining
[2021-10-29 17:30:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:37] Number of windows considered: 1...
[2021-10-29 17:30:37] Bias-correcting 1 members separately...
[2021-10-29 17:30:37] Done.
Validation 18, 4 remaining
[2021-10-29 17:30:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:39] Number of windows considered: 1...
[2021-10-29 17:30:39] Bias-correcting 1 members separately...
[2021-10-29 17:30:39] Done.
Validation 19, 3 remaining
[2021-10-29 17:30:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:40] Number of windows considered: 1...
[2021-10-29 17:30:40] Bias-correcting 1 members separately...
[2021-10-29 17:30:40] Done.
Validation 20, 2 remaining
[2021-10-29 17:30:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:41] Number of windows considered: 1...
[2021-10-29 17:30:41] Bias-correcting 1 members separately...
[2021-10-29 17:30:41] Done.
Validation 21, 1 remaining
[2021-10-29 17:30:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:42] Number of windows considered: 1...
[2021-10-29 17:30:42] Bias-correcting 1 members separately...
[2021-10-29 17:30:42] Done.
Validation 22, 0 remaining
[2021-10-29 17:30:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:43] Number of windows considered: 1...
[2021-10-29 17:30:43] Bias-correcting 1 members separately...
[2021-10-29 17:30:43] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 17:30:44] Performing annual aggregation...
[2021-10-29 17:30:44] Done.
[2021-10-29 17:30:44] - Computing climatology...
[2021-10-29 17:30:44] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.eqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:30:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:45] Number of windows considered: 1...
[2021-10-29 17:30:45] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:30:45] Done.
Validation 2, 20 remaining
[2021-10-29 17:30:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:46] Number of windows considered: 1...
[2021-10-29 17:30:46] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:30:46] Done.
Validation 3, 19 remaining
[2021-10-29 17:30:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:47] Number of windows considered: 1...
[2021-10-29 17:30:47] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:30:47] Done.
Validation 4, 18 remaining
[2021-10-29 17:30:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:48] Number of windows considered: 1...
[2021-10-29 17:30:48] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:30:49] Done.
Validation 5, 17 remaining
[2021-10-29 17:30:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:49] Number of windows considered: 1...
[2021-10-29 17:30:50] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:30:50] Done.
Validation 6, 16 remaining
[2021-10-29 17:30:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:50] Number of windows considered: 1...
[2021-10-29 17:30:50] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:30:51] Done.
Validation 7, 15 remaining
[2021-10-29 17:30:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:52] Number of windows considered: 1...
[2021-10-29 17:30:52] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:30:52] Done.
Validation 8, 14 remaining
[2021-10-29 17:30:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:53] Number of windows considered: 1...
[2021-10-29 17:30:53] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:30:53] Done.
Validation 9, 13 remaining
[2021-10-29 17:30:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:54] Number of windows considered: 1...
[2021-10-29 17:30:54] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:30:54] Done.
Validation 10, 12 remaining
[2021-10-29 17:30:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:55] Number of windows considered: 1...
[2021-10-29 17:30:55] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:30:55] Done.
Validation 11, 11 remaining
[2021-10-29 17:30:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:56] Number of windows considered: 1...
[2021-10-29 17:30:56] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:30:57] Done.
Validation 12, 10 remaining
[2021-10-29 17:30:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:58] Number of windows considered: 1...
[2021-10-29 17:30:58] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:30:58] Done.
Validation 13, 9 remaining
[2021-10-29 17:30:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:30:59] Number of windows considered: 1...
[2021-10-29 17:30:59] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:30:59] Done.
Validation 14, 8 remaining
[2021-10-29 17:31:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:00] Number of windows considered: 1...
[2021-10-29 17:31:00] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:00] Done.
Validation 15, 7 remaining
[2021-10-29 17:31:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:01] Number of windows considered: 1...
[2021-10-29 17:31:01] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:31:01] Done.
Validation 16, 6 remaining
[2021-10-29 17:31:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:02] Number of windows considered: 1...
[2021-10-29 17:31:02] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:31:02] Done.
Validation 17, 5 remaining
[2021-10-29 17:31:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:03] Number of windows considered: 1...
[2021-10-29 17:31:03] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:03] Done.
Validation 18, 4 remaining
[2021-10-29 17:31:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:04] Number of windows considered: 1...
[2021-10-29 17:31:04] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:31:05] Done.
Validation 19, 3 remaining
[2021-10-29 17:31:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:05] Number of windows considered: 1...
[2021-10-29 17:31:05] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:06] Done.
Validation 20, 2 remaining
[2021-10-29 17:31:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:07] Number of windows considered: 1...
[2021-10-29 17:31:07] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:07] Done.
Validation 21, 1 remaining
[2021-10-29 17:31:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:08] Number of windows considered: 1...
[2021-10-29 17:31:08] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:08] Done.
Validation 22, 0 remaining
[2021-10-29 17:31:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:09] Number of windows considered: 1...
[2021-10-29 17:31:09] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:09] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 17:31:10] Performing annual aggregation...
[2021-10-29 17:31:10] Done.
[2021-10-29 17:31:10] - Computing climatology...
[2021-10-29 17:31:10] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:31:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:11] Number of windows considered: 1...
[2021-10-29 17:31:11] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:11] Done.
Validation 2, 20 remaining
[2021-10-29 17:31:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:12] Number of windows considered: 1...
[2021-10-29 17:31:12] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:12] Done.
Validation 3, 19 remaining
[2021-10-29 17:31:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:13] Number of windows considered: 1...
[2021-10-29 17:31:13] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:13] Done.
Validation 4, 18 remaining
[2021-10-29 17:31:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:15] Number of windows considered: 1...
[2021-10-29 17:31:15] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:15] Done.
Validation 5, 17 remaining
[2021-10-29 17:31:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:16] Number of windows considered: 1...
[2021-10-29 17:31:16] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:16] Done.
Validation 6, 16 remaining
[2021-10-29 17:31:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:17] Number of windows considered: 1...
[2021-10-29 17:31:17] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:17] Done.
Validation 7, 15 remaining
[2021-10-29 17:31:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:18] Number of windows considered: 1...
[2021-10-29 17:31:18] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:18] Done.
Validation 8, 14 remaining
[2021-10-29 17:31:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:19] Number of windows considered: 1...
[2021-10-29 17:31:19] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:19] Done.
Validation 9, 13 remaining
[2021-10-29 17:31:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:21] Number of windows considered: 1...
[2021-10-29 17:31:21] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:21] Done.
Validation 10, 12 remaining
[2021-10-29 17:31:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:22] Number of windows considered: 1...
[2021-10-29 17:31:22] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:22] Done.
Validation 11, 11 remaining
[2021-10-29 17:31:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:23] Number of windows considered: 1...
[2021-10-29 17:31:23] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:23] Done.
Validation 12, 10 remaining
[2021-10-29 17:31:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:24] Number of windows considered: 1...
[2021-10-29 17:31:24] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:24] Done.
Validation 13, 9 remaining
[2021-10-29 17:31:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:26] Number of windows considered: 1...
[2021-10-29 17:31:26] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:26] Done.
Validation 14, 8 remaining
[2021-10-29 17:31:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:27] Number of windows considered: 1...
[2021-10-29 17:31:27] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:27] Done.
Validation 15, 7 remaining
[2021-10-29 17:31:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:28] Number of windows considered: 1...
[2021-10-29 17:31:28] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:28] Done.
Validation 16, 6 remaining
[2021-10-29 17:31:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:29] Number of windows considered: 1...
[2021-10-29 17:31:29] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:29] Done.
Validation 17, 5 remaining
[2021-10-29 17:31:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:30] Number of windows considered: 1...
[2021-10-29 17:31:30] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:31] Done.
Validation 18, 4 remaining
[2021-10-29 17:31:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:32] Number of windows considered: 1...
[2021-10-29 17:31:32] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:32] Done.
Validation 19, 3 remaining
[2021-10-29 17:31:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:33] Number of windows considered: 1...
[2021-10-29 17:31:33] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:33] Done.
Validation 20, 2 remaining
[2021-10-29 17:31:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:34] Number of windows considered: 1...
[2021-10-29 17:31:34] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:34] Done.
Validation 21, 1 remaining
[2021-10-29 17:31:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:35] Number of windows considered: 1...
[2021-10-29 17:31:35] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:35] Done.
Validation 22, 0 remaining
[2021-10-29 17:31:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:36] Number of windows considered: 1...
[2021-10-29 17:31:36] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:31:37] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-10-29 17:31:37] Performing annual aggregation...
[2021-10-29 17:31:37] Done.
[2021-10-29 17:31:37] - Computing climatology...
[2021-10-29 17:31:37] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm2.cl2 <- index.cal.station.cl2
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores
PQM-WT2 EQM-WT2 GPQM-WT2 GPQM2-WT2
0.8255456 0.6103610 0.4813834 0.4550170
scores.st6.wt2 <- scores
WT3
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))
station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
[2021-10-29 17:31:38] Performing annual aggregation...
[2021-10-29 17:31:38] Done.
[2021-10-29 17:31:38] - Computing climatology...
[2021-10-29 17:31:38] - Done.
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)
index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
[2021-10-29 17:31:38] Performing annual aggregation...
[2021-10-29 17:31:38] Done.
[2021-10-29 17:31:38] - Computing climatology...
[2021-10-29 17:31:38] - Done.
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")
station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:31:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:40] Number of windows considered: 1...
[2021-10-29 17:31:40] Bias-correcting 1 members separately...
[2021-10-29 17:31:40] Done.
Validation 2, 20 remaining
[2021-10-29 17:31:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:41] Number of windows considered: 1...
[2021-10-29 17:31:41] Bias-correcting 1 members separately...
[2021-10-29 17:31:41] Done.
Validation 3, 19 remaining
[2021-10-29 17:31:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:42] Number of windows considered: 1...
[2021-10-29 17:31:42] Bias-correcting 1 members separately...
[2021-10-29 17:31:42] Done.
Validation 4, 18 remaining
[2021-10-29 17:31:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:43] Number of windows considered: 1...
[2021-10-29 17:31:43] Bias-correcting 1 members separately...
[2021-10-29 17:31:43] Done.
Validation 5, 17 remaining
[2021-10-29 17:31:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:44] Number of windows considered: 1...
[2021-10-29 17:31:44] Bias-correcting 1 members separately...
[2021-10-29 17:31:44] Done.
Validation 6, 16 remaining
[2021-10-29 17:31:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:45] Number of windows considered: 1...
[2021-10-29 17:31:45] Bias-correcting 1 members separately...
[2021-10-29 17:31:46] Done.
Validation 7, 15 remaining
[2021-10-29 17:31:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:47] Number of windows considered: 1...
[2021-10-29 17:31:47] Bias-correcting 1 members separately...
[2021-10-29 17:31:47] Done.
Validation 8, 14 remaining
[2021-10-29 17:31:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:48] Number of windows considered: 1...
[2021-10-29 17:31:48] Bias-correcting 1 members separately...
[2021-10-29 17:31:48] Done.
Validation 9, 13 remaining
[2021-10-29 17:31:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:49] Number of windows considered: 1...
[2021-10-29 17:31:49] Bias-correcting 1 members separately...
[2021-10-29 17:31:49] Done.
Validation 10, 12 remaining
[2021-10-29 17:31:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:50] Number of windows considered: 1...
[2021-10-29 17:31:50] Bias-correcting 1 members separately...
[2021-10-29 17:31:51] Done.
Validation 11, 11 remaining
[2021-10-29 17:31:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:52] Number of windows considered: 1...
[2021-10-29 17:31:52] Bias-correcting 1 members separately...
[2021-10-29 17:31:52] Done.
Validation 12, 10 remaining
[2021-10-29 17:31:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:53] Number of windows considered: 1...
[2021-10-29 17:31:53] Bias-correcting 1 members separately...
[2021-10-29 17:31:53] Done.
Validation 13, 9 remaining
[2021-10-29 17:31:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:54] Number of windows considered: 1...
[2021-10-29 17:31:54] Bias-correcting 1 members separately...
[2021-10-29 17:31:55] Done.
Validation 14, 8 remaining
[2021-10-29 17:31:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:56] Number of windows considered: 1...
[2021-10-29 17:31:56] Bias-correcting 1 members separately...
[2021-10-29 17:31:56] Done.
Validation 15, 7 remaining
[2021-10-29 17:31:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:57] Number of windows considered: 1...
[2021-10-29 17:31:57] Bias-correcting 1 members separately...
[2021-10-29 17:31:57] Done.
Validation 16, 6 remaining
[2021-10-29 17:31:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:31:58] Number of windows considered: 1...
[2021-10-29 17:31:58] Bias-correcting 1 members separately...
[2021-10-29 17:31:58] Done.
Validation 17, 5 remaining
[2021-10-29 17:32:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:00] Number of windows considered: 1...
[2021-10-29 17:32:00] Bias-correcting 1 members separately...
[2021-10-29 17:32:00] Done.
Validation 18, 4 remaining
[2021-10-29 17:32:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:01] Number of windows considered: 1...
[2021-10-29 17:32:01] Bias-correcting 1 members separately...
[2021-10-29 17:32:01] Done.
Validation 19, 3 remaining
[2021-10-29 17:32:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:02] Number of windows considered: 1...
[2021-10-29 17:32:02] Bias-correcting 1 members separately...
[2021-10-29 17:32:02] Done.
Validation 20, 2 remaining
[2021-10-29 17:32:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:03] Number of windows considered: 1...
[2021-10-29 17:32:03] Bias-correcting 1 members separately...
[2021-10-29 17:32:04] Done.
Validation 21, 1 remaining
[2021-10-29 17:32:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:05] Number of windows considered: 1...
[2021-10-29 17:32:05] Bias-correcting 1 members separately...
[2021-10-29 17:32:05] Done.
Validation 22, 0 remaining
[2021-10-29 17:32:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:06] Number of windows considered: 1...
[2021-10-29 17:32:06] Bias-correcting 1 members separately...
[2021-10-29 17:32:06] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 17:32:06] Performing annual aggregation...
[2021-10-29 17:32:06] Done.
[2021-10-29 17:32:06] - Computing climatology...
[2021-10-29 17:32:06] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.pqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:32:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:08] Number of windows considered: 1...
[2021-10-29 17:32:08] Bias-correcting 1 members separately...
[2021-10-29 17:32:08] Done.
Validation 2, 20 remaining
[2021-10-29 17:32:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:10] Number of windows considered: 1...
[2021-10-29 17:32:10] Bias-correcting 1 members separately...
[2021-10-29 17:32:10] Done.
Validation 3, 19 remaining
[2021-10-29 17:32:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:11] Number of windows considered: 1...
[2021-10-29 17:32:11] Bias-correcting 1 members separately...
[2021-10-29 17:32:11] Done.
Validation 4, 18 remaining
[2021-10-29 17:32:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:12] Number of windows considered: 1...
[2021-10-29 17:32:12] Bias-correcting 1 members separately...
[2021-10-29 17:32:12] Done.
Validation 5, 17 remaining
[2021-10-29 17:32:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:13] Number of windows considered: 1...
[2021-10-29 17:32:13] Bias-correcting 1 members separately...
[2021-10-29 17:32:13] Done.
Validation 6, 16 remaining
[2021-10-29 17:32:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:14] Number of windows considered: 1...
[2021-10-29 17:32:14] Bias-correcting 1 members separately...
[2021-10-29 17:32:14] Done.
Validation 7, 15 remaining
[2021-10-29 17:32:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:15] Number of windows considered: 1...
[2021-10-29 17:32:15] Bias-correcting 1 members separately...
[2021-10-29 17:32:15] Done.
Validation 8, 14 remaining
[2021-10-29 17:32:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:16] Number of windows considered: 1...
[2021-10-29 17:32:16] Bias-correcting 1 members separately...
[2021-10-29 17:32:16] Done.
Validation 9, 13 remaining
[2021-10-29 17:32:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:17] Number of windows considered: 1...
[2021-10-29 17:32:17] Bias-correcting 1 members separately...
[2021-10-29 17:32:17] Done.
Validation 10, 12 remaining
[2021-10-29 17:32:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:18] Number of windows considered: 1...
[2021-10-29 17:32:18] Bias-correcting 1 members separately...
[2021-10-29 17:32:18] Done.
Validation 11, 11 remaining
[2021-10-29 17:32:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:19] Number of windows considered: 1...
[2021-10-29 17:32:19] Bias-correcting 1 members separately...
[2021-10-29 17:32:19] Done.
Validation 12, 10 remaining
[2021-10-29 17:32:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:20] Number of windows considered: 1...
[2021-10-29 17:32:20] Bias-correcting 1 members separately...
[2021-10-29 17:32:20] Done.
Validation 13, 9 remaining
[2021-10-29 17:32:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:21] Number of windows considered: 1...
[2021-10-29 17:32:21] Bias-correcting 1 members separately...
[2021-10-29 17:32:21] Done.
Validation 14, 8 remaining
[2021-10-29 17:32:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:22] Number of windows considered: 1...
[2021-10-29 17:32:22] Bias-correcting 1 members separately...
[2021-10-29 17:32:22] Done.
Validation 15, 7 remaining
[2021-10-29 17:32:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:23] Number of windows considered: 1...
[2021-10-29 17:32:23] Bias-correcting 1 members separately...
[2021-10-29 17:32:23] Done.
Validation 16, 6 remaining
[2021-10-29 17:32:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:24] Number of windows considered: 1...
[2021-10-29 17:32:24] Bias-correcting 1 members separately...
[2021-10-29 17:32:24] Done.
Validation 17, 5 remaining
[2021-10-29 17:32:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:25] Number of windows considered: 1...
[2021-10-29 17:32:25] Bias-correcting 1 members separately...
[2021-10-29 17:32:25] Done.
Validation 18, 4 remaining
[2021-10-29 17:32:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:26] Number of windows considered: 1...
[2021-10-29 17:32:26] Bias-correcting 1 members separately...
[2021-10-29 17:32:26] Done.
Validation 19, 3 remaining
[2021-10-29 17:32:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:27] Number of windows considered: 1...
[2021-10-29 17:32:27] Bias-correcting 1 members separately...
[2021-10-29 17:32:28] Done.
Validation 20, 2 remaining
[2021-10-29 17:32:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:29] Number of windows considered: 1...
[2021-10-29 17:32:29] Bias-correcting 1 members separately...
[2021-10-29 17:32:29] Done.
Validation 21, 1 remaining
[2021-10-29 17:32:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:30] Number of windows considered: 1...
[2021-10-29 17:32:30] Bias-correcting 1 members separately...
[2021-10-29 17:32:30] Done.
Validation 22, 0 remaining
[2021-10-29 17:32:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:31] Number of windows considered: 1...
[2021-10-29 17:32:31] Bias-correcting 1 members separately...
[2021-10-29 17:32:31] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 17:32:31] Performing annual aggregation...
[2021-10-29 17:32:31] Done.
[2021-10-29 17:32:31] - Computing climatology...
[2021-10-29 17:32:31] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.eqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:32:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:33] Number of windows considered: 1...
[2021-10-29 17:32:33] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:32:33] Done.
Validation 2, 20 remaining
[2021-10-29 17:32:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:34] Number of windows considered: 1...
[2021-10-29 17:32:34] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:34] Done.
Validation 3, 19 remaining
[2021-10-29 17:32:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:35] Number of windows considered: 1...
[2021-10-29 17:32:35] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:35] Done.
Validation 4, 18 remaining
[2021-10-29 17:32:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:36] Number of windows considered: 1...
[2021-10-29 17:32:36] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:36] Done.
Validation 5, 17 remaining
[2021-10-29 17:32:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:37] Number of windows considered: 1...
[2021-10-29 17:32:37] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:37] Done.
Validation 6, 16 remaining
[2021-10-29 17:32:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:38] Number of windows considered: 1...
[2021-10-29 17:32:38] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:38] Done.
Validation 7, 15 remaining
[2021-10-29 17:32:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:40] Number of windows considered: 1...
[2021-10-29 17:32:40] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:40] Done.
Validation 8, 14 remaining
[2021-10-29 17:32:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:41] Number of windows considered: 1...
[2021-10-29 17:32:41] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:41] Done.
Validation 9, 13 remaining
[2021-10-29 17:32:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:42] Number of windows considered: 1...
[2021-10-29 17:32:42] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:42] Done.
Validation 10, 12 remaining
[2021-10-29 17:32:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:43] Number of windows considered: 1...
[2021-10-29 17:32:43] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:32:43] Done.
Validation 11, 11 remaining
[2021-10-29 17:32:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:44] Number of windows considered: 1...
[2021-10-29 17:32:44] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:44] Done.
Validation 12, 10 remaining
[2021-10-29 17:32:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:45] Number of windows considered: 1...
[2021-10-29 17:32:45] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:45] Done.
Validation 13, 9 remaining
[2021-10-29 17:32:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:46] Number of windows considered: 1...
[2021-10-29 17:32:46] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:47] Done.
Validation 14, 8 remaining
[2021-10-29 17:32:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:48] Number of windows considered: 1...
[2021-10-29 17:32:48] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:48] Done.
Validation 15, 7 remaining
[2021-10-29 17:32:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:49] Number of windows considered: 1...
[2021-10-29 17:32:49] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:32:49] Done.
Validation 16, 6 remaining
[2021-10-29 17:32:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:50] Number of windows considered: 1...
[2021-10-29 17:32:50] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:50] Done.
Validation 17, 5 remaining
[2021-10-29 17:32:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:51] Number of windows considered: 1...
[2021-10-29 17:32:51] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:51] Done.
Validation 18, 4 remaining
[2021-10-29 17:32:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:52] Number of windows considered: 1...
[2021-10-29 17:32:52] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:32:52] Done.
Validation 19, 3 remaining
[2021-10-29 17:32:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:53] Number of windows considered: 1...
[2021-10-29 17:32:53] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:54] Done.
Validation 20, 2 remaining
[2021-10-29 17:32:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:55] Number of windows considered: 1...
[2021-10-29 17:32:55] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:55] Done.
Validation 21, 1 remaining
[2021-10-29 17:32:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:56] Number of windows considered: 1...
[2021-10-29 17:32:56] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:56] Done.
Validation 22, 0 remaining
[2021-10-29 17:32:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:57] Number of windows considered: 1...
[2021-10-29 17:32:57] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:32:57] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 17:32:58] Performing annual aggregation...
[2021-10-29 17:32:58] Done.
[2021-10-29 17:32:58] - Computing climatology...
[2021-10-29 17:32:58] - Done.
optimization may not have succeeded
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:32:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:32:59] Number of windows considered: 1...
[2021-10-29 17:32:59] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:32:59] Done.
Validation 2, 20 remaining
[2021-10-29 17:33:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:00] Number of windows considered: 1...
[2021-10-29 17:33:00] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:00] Done.
Validation 3, 19 remaining
[2021-10-29 17:33:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:01] Number of windows considered: 1...
[2021-10-29 17:33:01] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:01] Done.
Validation 4, 18 remaining
[2021-10-29 17:33:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:02] Number of windows considered: 1...
[2021-10-29 17:33:02] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:03] Done.
Validation 5, 17 remaining
[2021-10-29 17:33:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:04] Number of windows considered: 1...
[2021-10-29 17:33:04] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:04] Done.
Validation 6, 16 remaining
[2021-10-29 17:33:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:05] Number of windows considered: 1...
[2021-10-29 17:33:05] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:05] Done.
Validation 7, 15 remaining
[2021-10-29 17:33:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:06] Number of windows considered: 1...
[2021-10-29 17:33:06] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:06] Done.
Validation 8, 14 remaining
[2021-10-29 17:33:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:07] Number of windows considered: 1...
[2021-10-29 17:33:07] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:07] Done.
Validation 9, 13 remaining
[2021-10-29 17:33:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:08] Number of windows considered: 1...
[2021-10-29 17:33:08] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:08] Done.
Validation 10, 12 remaining
[2021-10-29 17:33:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:10] Number of windows considered: 1...
[2021-10-29 17:33:10] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:10] Done.
Validation 11, 11 remaining
[2021-10-29 17:33:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:11] Number of windows considered: 1...
[2021-10-29 17:33:11] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:11] Done.
Validation 12, 10 remaining
[2021-10-29 17:33:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:12] Number of windows considered: 1...
[2021-10-29 17:33:12] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:12] Done.
Validation 13, 9 remaining
[2021-10-29 17:33:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:13] Number of windows considered: 1...
[2021-10-29 17:33:13] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:13] Done.
Validation 14, 8 remaining
[2021-10-29 17:33:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:14] Number of windows considered: 1...
[2021-10-29 17:33:14] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:14] Done.
Validation 15, 7 remaining
[2021-10-29 17:33:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:16] Number of windows considered: 1...
[2021-10-29 17:33:16] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:16] Done.
Validation 16, 6 remaining
[2021-10-29 17:33:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:17] Number of windows considered: 1...
[2021-10-29 17:33:17] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:17] Done.
Validation 17, 5 remaining
[2021-10-29 17:33:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:18] Number of windows considered: 1...
[2021-10-29 17:33:18] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:18] Done.
Validation 18, 4 remaining
[2021-10-29 17:33:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:19] Number of windows considered: 1...
[2021-10-29 17:33:19] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:20] Done.
Validation 19, 3 remaining
[2021-10-29 17:33:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:21] Number of windows considered: 1...
[2021-10-29 17:33:21] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:21] Done.
Validation 20, 2 remaining
[2021-10-29 17:33:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:22] Number of windows considered: 1...
[2021-10-29 17:33:22] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:22] Done.
Validation 21, 1 remaining
[2021-10-29 17:33:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:23] Number of windows considered: 1...
[2021-10-29 17:33:23] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:23] Done.
Validation 22, 0 remaining
[2021-10-29 17:33:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:24] Number of windows considered: 1...
[2021-10-29 17:33:24] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:33:24] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-10-29 17:33:25] Performing annual aggregation...
[2021-10-29 17:33:25] Done.
[2021-10-29 17:33:25] - Computing climatology...
[2021-10-29 17:33:25] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm2.cl3 <- index.cal.station.cl3
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
PQM-WT3 EQM-WT3 GPQM2-WT3 GPQM-WT3
0.90583828 0.82010439 0.62537096 0.04607956
scores.st6.wt3 <- scores
WT4
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))
station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
[2021-10-29 17:33:26] Performing annual aggregation...
no non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Inf[2021-10-29 17:33:26] Done.
[2021-10-29 17:33:26] - Computing climatology...
[2021-10-29 17:33:26] - Done.
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)
index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
[2021-10-29 17:33:26] Performing annual aggregation...
[2021-10-29 17:33:26] Done.
[2021-10-29 17:33:26] - Computing climatology...
[2021-10-29 17:33:26] - Done.
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")
station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:33:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:27] Number of windows considered: 1...
[2021-10-29 17:33:27] Bias-correcting 1 members separately...
[2021-10-29 17:33:27] Done.
Validation 2, 20 remaining
[2021-10-29 17:33:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:28] Number of windows considered: 1...
[2021-10-29 17:33:28] Bias-correcting 1 members separately...
[2021-10-29 17:33:28] Done.
Validation 3, 19 remaining
[2021-10-29 17:33:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:29] Number of windows considered: 1...
[2021-10-29 17:33:29] Bias-correcting 1 members separately...
[2021-10-29 17:33:29] Done.
Validation 4, 18 remaining
[2021-10-29 17:33:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:30] Number of windows considered: 1...
[2021-10-29 17:33:30] Bias-correcting 1 members separately...
[2021-10-29 17:33:30] Done.
Validation 5, 17 remaining
[2021-10-29 17:33:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:31] Number of windows considered: 1...
[2021-10-29 17:33:31] Bias-correcting 1 members separately...
[2021-10-29 17:33:31] Done.
Validation 6, 16 remaining
[2021-10-29 17:33:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:32] Number of windows considered: 1...
[2021-10-29 17:33:32] Bias-correcting 1 members separately...
[2021-10-29 17:33:33] Done.
Validation 7, 15 remaining
[2021-10-29 17:33:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:34] Number of windows considered: 1...
[2021-10-29 17:33:34] Bias-correcting 1 members separately...
[2021-10-29 17:33:34] Done.
Validation 8, 14 remaining
[2021-10-29 17:33:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:35] Number of windows considered: 1...
[2021-10-29 17:33:35] Bias-correcting 1 members separately...
[2021-10-29 17:33:35] Done.
Validation 9, 13 remaining
[2021-10-29 17:33:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:36] Number of windows considered: 1...
[2021-10-29 17:33:36] Bias-correcting 1 members separately...
[2021-10-29 17:33:36] Done.
Validation 10, 12 remaining
[2021-10-29 17:33:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:37] Number of windows considered: 1...
[2021-10-29 17:33:37] Bias-correcting 1 members separately...
[2021-10-29 17:33:37] Done.
Validation 11, 11 remaining
[2021-10-29 17:33:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:38] Number of windows considered: 1...
[2021-10-29 17:33:38] Bias-correcting 1 members separately...
[2021-10-29 17:33:39] Done.
Validation 12, 10 remaining
[2021-10-29 17:33:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:40] Number of windows considered: 1...
[2021-10-29 17:33:40] Bias-correcting 1 members separately...
[2021-10-29 17:33:40] Done.
Validation 13, 9 remaining
[2021-10-29 17:33:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:41] Number of windows considered: 1...
[2021-10-29 17:33:41] Bias-correcting 1 members separately...
[2021-10-29 17:33:41] Done.
Validation 14, 8 remaining
[2021-10-29 17:33:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:42] Number of windows considered: 1...
[2021-10-29 17:33:42] Bias-correcting 1 members separately...
[2021-10-29 17:33:42] Done.
Validation 15, 7 remaining
[2021-10-29 17:33:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:43] Number of windows considered: 1...
[2021-10-29 17:33:43] Bias-correcting 1 members separately...
[2021-10-29 17:33:43] Done.
Validation 16, 6 remaining
[2021-10-29 17:33:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:45] Number of windows considered: 1...
[2021-10-29 17:33:45] Bias-correcting 1 members separately...
[2021-10-29 17:33:45] Done.
Validation 17, 5 remaining
[2021-10-29 17:33:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:46] Number of windows considered: 1...
[2021-10-29 17:33:46] Bias-correcting 1 members separately...
[2021-10-29 17:33:46] Done.
Validation 18, 4 remaining
[2021-10-29 17:33:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:47] Number of windows considered: 1...
[2021-10-29 17:33:47] Bias-correcting 1 members separately...
[2021-10-29 17:33:47] Done.
Validation 19, 3 remaining
[2021-10-29 17:33:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:48] Number of windows considered: 1...
[2021-10-29 17:33:48] Bias-correcting 1 members separately...
[2021-10-29 17:33:48] Done.
Validation 20, 2 remaining
[2021-10-29 17:33:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:49] Number of windows considered: 1...
[2021-10-29 17:33:49] Bias-correcting 1 members separately...
[2021-10-29 17:33:49] Done.
Validation 21, 1 remaining
[2021-10-29 17:33:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:50] Number of windows considered: 1...
[2021-10-29 17:33:50] Bias-correcting 1 members separately...
[2021-10-29 17:33:50] Done.
Validation 22, 0 remaining
[2021-10-29 17:33:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:52] Number of windows considered: 1...
[2021-10-29 17:33:52] Bias-correcting 1 members separately...
[2021-10-29 17:33:52] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 17:33:52] Performing annual aggregation...
[2021-10-29 17:33:52] Done.
[2021-10-29 17:33:52] - Computing climatology...
[2021-10-29 17:33:52] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.pqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:33:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:54] Number of windows considered: 1...
[2021-10-29 17:33:54] Bias-correcting 1 members separately...
[2021-10-29 17:33:54] Done.
Validation 2, 20 remaining
[2021-10-29 17:33:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:55] Number of windows considered: 1...
[2021-10-29 17:33:55] Bias-correcting 1 members separately...
[2021-10-29 17:33:55] Done.
Validation 3, 19 remaining
[2021-10-29 17:33:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:56] Number of windows considered: 1...
[2021-10-29 17:33:56] Bias-correcting 1 members separately...
[2021-10-29 17:33:56] Done.
Validation 4, 18 remaining
[2021-10-29 17:33:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:57] Number of windows considered: 1...
[2021-10-29 17:33:57] Bias-correcting 1 members separately...
[2021-10-29 17:33:57] Done.
Validation 5, 17 remaining
[2021-10-29 17:33:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:58] Number of windows considered: 1...
[2021-10-29 17:33:58] Bias-correcting 1 members separately...
[2021-10-29 17:33:58] Done.
Validation 6, 16 remaining
[2021-10-29 17:33:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:33:59] Number of windows considered: 1...
[2021-10-29 17:33:59] Bias-correcting 1 members separately...
[2021-10-29 17:33:59] Done.
Validation 7, 15 remaining
[2021-10-29 17:34:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:00] Number of windows considered: 1...
[2021-10-29 17:34:00] Bias-correcting 1 members separately...
[2021-10-29 17:34:00] Done.
Validation 8, 14 remaining
[2021-10-29 17:34:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:01] Number of windows considered: 1...
[2021-10-29 17:34:01] Bias-correcting 1 members separately...
[2021-10-29 17:34:01] Done.
Validation 9, 13 remaining
[2021-10-29 17:34:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:02] Number of windows considered: 1...
[2021-10-29 17:34:02] Bias-correcting 1 members separately...
[2021-10-29 17:34:02] Done.
Validation 10, 12 remaining
[2021-10-29 17:34:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:03] Number of windows considered: 1...
[2021-10-29 17:34:03] Bias-correcting 1 members separately...
[2021-10-29 17:34:03] Done.
Validation 11, 11 remaining
[2021-10-29 17:34:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:04] Number of windows considered: 1...
[2021-10-29 17:34:04] Bias-correcting 1 members separately...
[2021-10-29 17:34:04] Done.
Validation 12, 10 remaining
[2021-10-29 17:34:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:05] Number of windows considered: 1...
[2021-10-29 17:34:05] Bias-correcting 1 members separately...
[2021-10-29 17:34:05] Done.
Validation 13, 9 remaining
[2021-10-29 17:34:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:06] Number of windows considered: 1...
[2021-10-29 17:34:06] Bias-correcting 1 members separately...
[2021-10-29 17:34:07] Done.
Validation 14, 8 remaining
[2021-10-29 17:34:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:07] Number of windows considered: 1...
[2021-10-29 17:34:07] Bias-correcting 1 members separately...
[2021-10-29 17:34:08] Done.
Validation 15, 7 remaining
[2021-10-29 17:34:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:09] Number of windows considered: 1...
[2021-10-29 17:34:09] Bias-correcting 1 members separately...
[2021-10-29 17:34:09] Done.
Validation 16, 6 remaining
[2021-10-29 17:34:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:10] Number of windows considered: 1...
[2021-10-29 17:34:10] Bias-correcting 1 members separately...
[2021-10-29 17:34:10] Done.
Validation 17, 5 remaining
[2021-10-29 17:34:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:11] Number of windows considered: 1...
[2021-10-29 17:34:11] Bias-correcting 1 members separately...
[2021-10-29 17:34:11] Done.
Validation 18, 4 remaining
[2021-10-29 17:34:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:12] Number of windows considered: 1...
[2021-10-29 17:34:12] Bias-correcting 1 members separately...
[2021-10-29 17:34:12] Done.
Validation 19, 3 remaining
[2021-10-29 17:34:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:13] Number of windows considered: 1...
[2021-10-29 17:34:13] Bias-correcting 1 members separately...
[2021-10-29 17:34:13] Done.
Validation 20, 2 remaining
[2021-10-29 17:34:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:14] Number of windows considered: 1...
[2021-10-29 17:34:14] Bias-correcting 1 members separately...
[2021-10-29 17:34:14] Done.
Validation 21, 1 remaining
[2021-10-29 17:34:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:15] Number of windows considered: 1...
[2021-10-29 17:34:15] Bias-correcting 1 members separately...
[2021-10-29 17:34:15] Done.
Validation 22, 0 remaining
[2021-10-29 17:34:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:16] Number of windows considered: 1...
[2021-10-29 17:34:16] Bias-correcting 1 members separately...
[2021-10-29 17:34:16] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 17:34:17] Performing annual aggregation...
[2021-10-29 17:34:17] Done.
[2021-10-29 17:34:17] - Computing climatology...
[2021-10-29 17:34:17] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.eqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:34:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:18] Number of windows considered: 1...
[2021-10-29 17:34:18] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:34:18] Done.
Validation 2, 20 remaining
[2021-10-29 17:34:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:19] Number of windows considered: 1...
[2021-10-29 17:34:19] Bias-correcting 1 members separately...
NaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:34:20] Done.
Validation 3, 19 remaining
[2021-10-29 17:34:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:20] Number of windows considered: 1...
[2021-10-29 17:34:20] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:34:21] Done.
Validation 4, 18 remaining
[2021-10-29 17:34:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:22] Number of windows considered: 1...
[2021-10-29 17:34:22] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:34:22] Done.
Validation 5, 17 remaining
[2021-10-29 17:34:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:23] Number of windows considered: 1...
[2021-10-29 17:34:23] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:34:23] Done.
Validation 6, 16 remaining
[2021-10-29 17:34:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:24] Number of windows considered: 1...
[2021-10-29 17:34:24] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:34:24] Done.
Validation 7, 15 remaining
[2021-10-29 17:34:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:25] Number of windows considered: 1...
[2021-10-29 17:34:25] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:34:25] Done.
Validation 8, 14 remaining
[2021-10-29 17:34:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:26] Number of windows considered: 1...
[2021-10-29 17:34:26] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:34:27] Done.
Validation 9, 13 remaining
[2021-10-29 17:34:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:28] Number of windows considered: 1...
[2021-10-29 17:34:28] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:34:28] Done.
Validation 10, 12 remaining
[2021-10-29 17:34:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:29] Number of windows considered: 1...
[2021-10-29 17:34:29] Bias-correcting 1 members separately...
NaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:34:29] Done.
Validation 11, 11 remaining
[2021-10-29 17:34:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:30] Number of windows considered: 1...
[2021-10-29 17:34:30] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:34:30] Done.
Validation 12, 10 remaining
[2021-10-29 17:34:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:31] Number of windows considered: 1...
[2021-10-29 17:34:31] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:34:31] Done.
Validation 13, 9 remaining
[2021-10-29 17:34:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:32] Number of windows considered: 1...
[2021-10-29 17:34:32] Bias-correcting 1 members separately...
NaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:34:32] Done.
Validation 14, 8 remaining
[2021-10-29 17:34:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:33] Number of windows considered: 1...
[2021-10-29 17:34:33] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:34:34] Done.
Validation 15, 7 remaining
[2021-10-29 17:34:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:35] Number of windows considered: 1...
[2021-10-29 17:34:35] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:34:35] Done.
Validation 16, 6 remaining
[2021-10-29 17:34:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:36] Number of windows considered: 1...
[2021-10-29 17:34:36] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:34:36] Done.
Validation 17, 5 remaining
[2021-10-29 17:34:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:37] Number of windows considered: 1...
[2021-10-29 17:34:37] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:34:37] Done.
Validation 18, 4 remaining
[2021-10-29 17:34:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:38] Number of windows considered: 1...
[2021-10-29 17:34:38] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:34:38] Done.
Validation 19, 3 remaining
[2021-10-29 17:34:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:39] Number of windows considered: 1...
[2021-10-29 17:34:39] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-10-29 17:34:39] Done.
Validation 20, 2 remaining
[2021-10-29 17:34:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:41] Number of windows considered: 1...
[2021-10-29 17:34:41] Bias-correcting 1 members separately...
NaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:34:41] Done.
Validation 21, 1 remaining
[2021-10-29 17:34:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:42] Number of windows considered: 1...
[2021-10-29 17:34:42] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:34:42] Done.
Validation 22, 0 remaining
[2021-10-29 17:34:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:43] Number of windows considered: 1...
[2021-10-29 17:34:43] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:34:43] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 17:34:44] Performing annual aggregation...
[2021-10-29 17:34:44] Done.
[2021-10-29 17:34:44] - Computing climatology...
[2021-10-29 17:34:44] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:34:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:45] Number of windows considered: 1...
[2021-10-29 17:34:45] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:34:45] Done.
Validation 2, 20 remaining
[2021-10-29 17:34:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:46] Number of windows considered: 1...
[2021-10-29 17:34:46] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:34:46] Done.
Validation 3, 19 remaining
[2021-10-29 17:34:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:48] Number of windows considered: 1...
[2021-10-29 17:34:48] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:34:48] Done.
Validation 4, 18 remaining
[2021-10-29 17:34:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:49] Number of windows considered: 1...
[2021-10-29 17:34:49] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:34:49] Done.
Validation 5, 17 remaining
[2021-10-29 17:34:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:50] Number of windows considered: 1...
[2021-10-29 17:34:50] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:34:50] Done.
Validation 6, 16 remaining
[2021-10-29 17:34:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:51] Number of windows considered: 1...
[2021-10-29 17:34:51] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:34:51] Done.
Validation 7, 15 remaining
[2021-10-29 17:34:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:52] Number of windows considered: 1...
[2021-10-29 17:34:52] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:34:52] Done.
Validation 8, 14 remaining
[2021-10-29 17:34:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:53] Number of windows considered: 1...
[2021-10-29 17:34:53] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:34:53] Done.
Validation 9, 13 remaining
[2021-10-29 17:34:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:55] Number of windows considered: 1...
[2021-10-29 17:34:55] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:34:55] Done.
Validation 10, 12 remaining
[2021-10-29 17:34:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:56] Number of windows considered: 1...
[2021-10-29 17:34:56] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:34:56] Done.
Validation 11, 11 remaining
[2021-10-29 17:34:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:57] Number of windows considered: 1...
[2021-10-29 17:34:57] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:34:57] Done.
Validation 12, 10 remaining
[2021-10-29 17:34:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:58] Number of windows considered: 1...
[2021-10-29 17:34:58] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:34:58] Done.
Validation 13, 9 remaining
[2021-10-29 17:34:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:34:59] Number of windows considered: 1...
[2021-10-29 17:34:59] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:35:00] Done.
Validation 14, 8 remaining
[2021-10-29 17:35:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:01] Number of windows considered: 1...
[2021-10-29 17:35:01] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:35:01] Done.
Validation 15, 7 remaining
[2021-10-29 17:35:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:02] Number of windows considered: 1...
[2021-10-29 17:35:02] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:35:02] Done.
Validation 16, 6 remaining
[2021-10-29 17:35:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:03] Number of windows considered: 1...
[2021-10-29 17:35:03] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:35:03] Done.
Validation 17, 5 remaining
[2021-10-29 17:35:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:04] Number of windows considered: 1...
[2021-10-29 17:35:04] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:35:04] Done.
Validation 18, 4 remaining
[2021-10-29 17:35:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:06] Number of windows considered: 1...
[2021-10-29 17:35:06] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:35:06] Done.
Validation 19, 3 remaining
[2021-10-29 17:35:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:07] Number of windows considered: 1...
[2021-10-29 17:35:07] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:35:07] Done.
Validation 20, 2 remaining
[2021-10-29 17:35:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:08] Number of windows considered: 1...
[2021-10-29 17:35:08] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:35:08] Done.
Validation 21, 1 remaining
[2021-10-29 17:35:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:09] Number of windows considered: 1...
[2021-10-29 17:35:09] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:35:09] Done.
Validation 22, 0 remaining
[2021-10-29 17:35:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:10] Number of windows considered: 1...
[2021-10-29 17:35:10] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:35:10] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-10-29 17:35:11] Performing annual aggregation...
[2021-10-29 17:35:11] Done.
[2021-10-29 17:35:11] - Computing climatology...
[2021-10-29 17:35:11] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm2.cl4 <- index.cal.station.cl4
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)
scores
EQM-WT4 PQM-WT4 GPQM2-WT4 GPQM-WT4
0.80308711 0.61524693 0.61177966 0.07945782
scores.st6.wt4 <- scores
WT5
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))
station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
[2021-10-29 17:35:12] Performing annual aggregation...
no non-missing arguments to max; returning -Inf[2021-10-29 17:35:12] Done.
[2021-10-29 17:35:12] - Computing climatology...
[2021-10-29 17:35:12] - Done.
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)
index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
[2021-10-29 17:35:12] Performing annual aggregation...
[2021-10-29 17:35:12] Done.
[2021-10-29 17:35:12] - Computing climatology...
[2021-10-29 17:35:12] - Done.
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")
station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:35:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:13] Number of windows considered: 1...
[2021-10-29 17:35:13] Bias-correcting 1 members separately...
[2021-10-29 17:35:14] Done.
Validation 2, 20 remaining
[2021-10-29 17:35:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:15] Number of windows considered: 1...
[2021-10-29 17:35:15] Bias-correcting 1 members separately...
[2021-10-29 17:35:15] Done.
Validation 3, 19 remaining
[2021-10-29 17:35:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:16] Number of windows considered: 1...
[2021-10-29 17:35:16] Bias-correcting 1 members separately...
[2021-10-29 17:35:16] Done.
Validation 4, 18 remaining
[2021-10-29 17:35:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:17] Number of windows considered: 1...
[2021-10-29 17:35:17] Bias-correcting 1 members separately...
[2021-10-29 17:35:17] Done.
Validation 5, 17 remaining
[2021-10-29 17:35:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:18] Number of windows considered: 1...
[2021-10-29 17:35:18] Bias-correcting 1 members separately...
[2021-10-29 17:35:18] Done.
Validation 6, 16 remaining
[2021-10-29 17:35:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:19] Number of windows considered: 1...
[2021-10-29 17:35:19] Bias-correcting 1 members separately...
[2021-10-29 17:35:19] Done.
Validation 7, 15 remaining
[2021-10-29 17:35:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:20] Number of windows considered: 1...
[2021-10-29 17:35:20] Bias-correcting 1 members separately...
[2021-10-29 17:35:20] Done.
Validation 8, 14 remaining
[2021-10-29 17:35:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:21] Number of windows considered: 1...
[2021-10-29 17:35:21] Bias-correcting 1 members separately...
[2021-10-29 17:35:21] Done.
Validation 9, 13 remaining
[2021-10-29 17:35:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:22] Number of windows considered: 1...
[2021-10-29 17:35:22] Bias-correcting 1 members separately...
[2021-10-29 17:35:22] Done.
Validation 10, 12 remaining
[2021-10-29 17:35:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:24] Number of windows considered: 1...
[2021-10-29 17:35:24] Bias-correcting 1 members separately...
[2021-10-29 17:35:24] Done.
Validation 11, 11 remaining
[2021-10-29 17:35:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:25] Number of windows considered: 1...
[2021-10-29 17:35:25] Bias-correcting 1 members separately...
[2021-10-29 17:35:25] Done.
Validation 12, 10 remaining
[2021-10-29 17:35:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:26] Number of windows considered: 1...
[2021-10-29 17:35:26] Bias-correcting 1 members separately...
[2021-10-29 17:35:26] Done.
Validation 13, 9 remaining
[2021-10-29 17:35:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:27] Number of windows considered: 1...
[2021-10-29 17:35:27] Bias-correcting 1 members separately...
[2021-10-29 17:35:27] Done.
Validation 14, 8 remaining
[2021-10-29 17:35:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:29] Number of windows considered: 1...
[2021-10-29 17:35:29] Bias-correcting 1 members separately...
[2021-10-29 17:35:29] Done.
Validation 15, 7 remaining
[2021-10-29 17:35:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:30] Number of windows considered: 1...
[2021-10-29 17:35:30] Bias-correcting 1 members separately...
[2021-10-29 17:35:30] Done.
Validation 16, 6 remaining
[2021-10-29 17:35:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:31] Number of windows considered: 1...
[2021-10-29 17:35:31] Bias-correcting 1 members separately...
[2021-10-29 17:35:31] Done.
Validation 17, 5 remaining
[2021-10-29 17:35:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:32] Number of windows considered: 1...
[2021-10-29 17:35:32] Bias-correcting 1 members separately...
[2021-10-29 17:35:32] Done.
Validation 18, 4 remaining
[2021-10-29 17:35:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:33] Number of windows considered: 1...
[2021-10-29 17:35:33] Bias-correcting 1 members separately...
[2021-10-29 17:35:33] Done.
Validation 19, 3 remaining
[2021-10-29 17:35:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:34] Number of windows considered: 1...
[2021-10-29 17:35:34] Bias-correcting 1 members separately...
[2021-10-29 17:35:34] Done.
Validation 20, 2 remaining
[2021-10-29 17:35:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:35] Number of windows considered: 1...
[2021-10-29 17:35:35] Bias-correcting 1 members separately...
[2021-10-29 17:35:35] Done.
Validation 21, 1 remaining
[2021-10-29 17:35:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:36] Number of windows considered: 1...
[2021-10-29 17:35:36] Bias-correcting 1 members separately...
[2021-10-29 17:35:36] Done.
Validation 22, 0 remaining
[2021-10-29 17:35:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:37] Number of windows considered: 1...
[2021-10-29 17:35:37] Bias-correcting 1 members separately...
[2021-10-29 17:35:37] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 17:35:38] Performing annual aggregation...
[2021-10-29 17:35:38] Done.
[2021-10-29 17:35:38] - Computing climatology...
[2021-10-29 17:35:38] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.pqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:35:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:39] Number of windows considered: 1...
[2021-10-29 17:35:39] Bias-correcting 1 members separately...
[2021-10-29 17:35:39] Done.
Validation 2, 20 remaining
[2021-10-29 17:35:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:40] Number of windows considered: 1...
[2021-10-29 17:35:40] Bias-correcting 1 members separately...
[2021-10-29 17:35:40] Done.
Validation 3, 19 remaining
[2021-10-29 17:35:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:41] Number of windows considered: 1...
[2021-10-29 17:35:41] Bias-correcting 1 members separately...
[2021-10-29 17:35:41] Done.
Validation 4, 18 remaining
[2021-10-29 17:35:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:42] Number of windows considered: 1...
[2021-10-29 17:35:42] Bias-correcting 1 members separately...
[2021-10-29 17:35:42] Done.
Validation 5, 17 remaining
[2021-10-29 17:35:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:43] Number of windows considered: 1...
[2021-10-29 17:35:43] Bias-correcting 1 members separately...
[2021-10-29 17:35:43] Done.
Validation 6, 16 remaining
[2021-10-29 17:35:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:44] Number of windows considered: 1...
[2021-10-29 17:35:44] Bias-correcting 1 members separately...
[2021-10-29 17:35:44] Done.
Validation 7, 15 remaining
[2021-10-29 17:35:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:45] Number of windows considered: 1...
[2021-10-29 17:35:45] Bias-correcting 1 members separately...
[2021-10-29 17:35:45] Done.
Validation 8, 14 remaining
[2021-10-29 17:35:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:46] Number of windows considered: 1...
[2021-10-29 17:35:46] Bias-correcting 1 members separately...
[2021-10-29 17:35:46] Done.
Validation 9, 13 remaining
[2021-10-29 17:35:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:47] Number of windows considered: 1...
[2021-10-29 17:35:47] Bias-correcting 1 members separately...
[2021-10-29 17:35:48] Done.
Validation 10, 12 remaining
[2021-10-29 17:35:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:49] Number of windows considered: 1...
[2021-10-29 17:35:49] Bias-correcting 1 members separately...
[2021-10-29 17:35:49] Done.
Validation 11, 11 remaining
[2021-10-29 17:35:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:50] Number of windows considered: 1...
[2021-10-29 17:35:50] Bias-correcting 1 members separately...
[2021-10-29 17:35:50] Done.
Validation 12, 10 remaining
[2021-10-29 17:35:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:51] Number of windows considered: 1...
[2021-10-29 17:35:51] Bias-correcting 1 members separately...
[2021-10-29 17:35:51] Done.
Validation 13, 9 remaining
[2021-10-29 17:35:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:52] Number of windows considered: 1...
[2021-10-29 17:35:52] Bias-correcting 1 members separately...
[2021-10-29 17:35:52] Done.
Validation 14, 8 remaining
[2021-10-29 17:35:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:53] Number of windows considered: 1...
[2021-10-29 17:35:53] Bias-correcting 1 members separately...
[2021-10-29 17:35:53] Done.
Validation 15, 7 remaining
[2021-10-29 17:35:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:54] Number of windows considered: 1...
[2021-10-29 17:35:54] Bias-correcting 1 members separately...
[2021-10-29 17:35:54] Done.
Validation 16, 6 remaining
[2021-10-29 17:35:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:55] Number of windows considered: 1...
[2021-10-29 17:35:55] Bias-correcting 1 members separately...
[2021-10-29 17:35:55] Done.
Validation 17, 5 remaining
[2021-10-29 17:35:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:56] Number of windows considered: 1...
[2021-10-29 17:35:56] Bias-correcting 1 members separately...
[2021-10-29 17:35:57] Done.
Validation 18, 4 remaining
[2021-10-29 17:35:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:58] Number of windows considered: 1...
[2021-10-29 17:35:58] Bias-correcting 1 members separately...
[2021-10-29 17:35:58] Done.
Validation 19, 3 remaining
[2021-10-29 17:35:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:35:59] Number of windows considered: 1...
[2021-10-29 17:35:59] Bias-correcting 1 members separately...
[2021-10-29 17:35:59] Done.
Validation 20, 2 remaining
[2021-10-29 17:36:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:00] Number of windows considered: 1...
[2021-10-29 17:36:00] Bias-correcting 1 members separately...
[2021-10-29 17:36:00] Done.
Validation 21, 1 remaining
[2021-10-29 17:36:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:01] Number of windows considered: 1...
[2021-10-29 17:36:01] Bias-correcting 1 members separately...
[2021-10-29 17:36:01] Done.
Validation 22, 0 remaining
[2021-10-29 17:36:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:02] Number of windows considered: 1...
[2021-10-29 17:36:02] Bias-correcting 1 members separately...
[2021-10-29 17:36:02] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 17:36:03] Performing annual aggregation...
[2021-10-29 17:36:03] Done.
[2021-10-29 17:36:03] - Computing climatology...
[2021-10-29 17:36:03] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.eqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:36:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:05] Number of windows considered: 1...
[2021-10-29 17:36:05] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:05] Done.
Validation 2, 20 remaining
[2021-10-29 17:36:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:06] Number of windows considered: 1...
[2021-10-29 17:36:06] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:06] Done.
Validation 3, 19 remaining
[2021-10-29 17:36:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:07] Number of windows considered: 1...
[2021-10-29 17:36:07] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:07] Done.
Validation 4, 18 remaining
[2021-10-29 17:36:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:08] Number of windows considered: 1...
[2021-10-29 17:36:08] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:08] Done.
Validation 5, 17 remaining
[2021-10-29 17:36:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:09] Number of windows considered: 1...
[2021-10-29 17:36:09] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:09] Done.
Validation 6, 16 remaining
[2021-10-29 17:36:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:10] Number of windows considered: 1...
[2021-10-29 17:36:10] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:11] Done.
Validation 7, 15 remaining
[2021-10-29 17:36:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:12] Number of windows considered: 1...
[2021-10-29 17:36:12] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:36:12] Done.
Validation 8, 14 remaining
[2021-10-29 17:36:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:13] Number of windows considered: 1...
[2021-10-29 17:36:13] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:13] Done.
Validation 9, 13 remaining
[2021-10-29 17:36:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:14] Number of windows considered: 1...
[2021-10-29 17:36:14] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:14] Done.
Validation 10, 12 remaining
[2021-10-29 17:36:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:15] Number of windows considered: 1...
[2021-10-29 17:36:15] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:15] Done.
Validation 11, 11 remaining
[2021-10-29 17:36:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:16] Number of windows considered: 1...
[2021-10-29 17:36:16] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:17] Done.
Validation 12, 10 remaining
[2021-10-29 17:36:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:18] Number of windows considered: 1...
[2021-10-29 17:36:18] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:18] Done.
Validation 13, 9 remaining
[2021-10-29 17:36:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:19] Number of windows considered: 1...
[2021-10-29 17:36:19] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:19] Done.
Validation 14, 8 remaining
[2021-10-29 17:36:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:20] Number of windows considered: 1...
[2021-10-29 17:36:20] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:20] Done.
Validation 15, 7 remaining
[2021-10-29 17:36:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:21] Number of windows considered: 1...
[2021-10-29 17:36:21] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:22] Done.
Validation 16, 6 remaining
[2021-10-29 17:36:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:23] Number of windows considered: 1...
[2021-10-29 17:36:23] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:23] Done.
Validation 17, 5 remaining
[2021-10-29 17:36:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:24] Number of windows considered: 1...
[2021-10-29 17:36:24] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:24] Done.
Validation 18, 4 remaining
[2021-10-29 17:36:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:25] Number of windows considered: 1...
[2021-10-29 17:36:25] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:25] Done.
Validation 19, 3 remaining
[2021-10-29 17:36:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:27] Number of windows considered: 1...
[2021-10-29 17:36:27] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-10-29 17:36:27] Done.
Validation 20, 2 remaining
[2021-10-29 17:36:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:28] Number of windows considered: 1...
[2021-10-29 17:36:28] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:28] Done.
Validation 21, 1 remaining
[2021-10-29 17:36:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:29] Number of windows considered: 1...
[2021-10-29 17:36:29] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:29] Done.
Validation 22, 0 remaining
[2021-10-29 17:36:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:30] Number of windows considered: 1...
[2021-10-29 17:36:30] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-10-29 17:36:30] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 17:36:31] Performing annual aggregation...
[2021-10-29 17:36:31] Done.
[2021-10-29 17:36:31] - Computing climatology...
[2021-10-29 17:36:31] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:36:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:33] Number of windows considered: 1...
[2021-10-29 17:36:33] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:33] Done.
Validation 2, 20 remaining
[2021-10-29 17:36:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:34] Number of windows considered: 1...
[2021-10-29 17:36:34] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:34] Done.
Validation 3, 19 remaining
[2021-10-29 17:36:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:35] Number of windows considered: 1...
[2021-10-29 17:36:35] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:35] Done.
Validation 4, 18 remaining
[2021-10-29 17:36:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:36] Number of windows considered: 1...
[2021-10-29 17:36:36] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:36] Done.
Validation 5, 17 remaining
[2021-10-29 17:36:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:38] Number of windows considered: 1...
[2021-10-29 17:36:38] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:38] Done.
Validation 6, 16 remaining
[2021-10-29 17:36:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:39] Number of windows considered: 1...
[2021-10-29 17:36:39] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:39] Done.
Validation 7, 15 remaining
[2021-10-29 17:36:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:40] Number of windows considered: 1...
[2021-10-29 17:36:40] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:40] Done.
Validation 8, 14 remaining
[2021-10-29 17:36:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:41] Number of windows considered: 1...
[2021-10-29 17:36:41] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:42] Done.
Validation 9, 13 remaining
[2021-10-29 17:36:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:43] Number of windows considered: 1...
[2021-10-29 17:36:43] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:43] Done.
Validation 10, 12 remaining
[2021-10-29 17:36:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:44] Number of windows considered: 1...
[2021-10-29 17:36:44] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:44] Done.
Validation 11, 11 remaining
[2021-10-29 17:36:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:45] Number of windows considered: 1...
[2021-10-29 17:36:45] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:46] Done.
Validation 12, 10 remaining
[2021-10-29 17:36:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:47] Number of windows considered: 1...
[2021-10-29 17:36:47] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:47] Done.
Validation 13, 9 remaining
[2021-10-29 17:36:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:48] Number of windows considered: 1...
[2021-10-29 17:36:48] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:48] Done.
Validation 14, 8 remaining
[2021-10-29 17:36:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:49] Number of windows considered: 1...
[2021-10-29 17:36:49] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:50] Done.
Validation 15, 7 remaining
[2021-10-29 17:36:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:51] Number of windows considered: 1...
[2021-10-29 17:36:51] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:51] Done.
Validation 16, 6 remaining
[2021-10-29 17:36:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:52] Number of windows considered: 1...
[2021-10-29 17:36:52] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:52] Done.
Validation 17, 5 remaining
[2021-10-29 17:36:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:53] Number of windows considered: 1...
[2021-10-29 17:36:53] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:53] Done.
Validation 18, 4 remaining
[2021-10-29 17:36:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:55] Number of windows considered: 1...
[2021-10-29 17:36:55] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:55] Done.
Validation 19, 3 remaining
[2021-10-29 17:36:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:56] Number of windows considered: 1...
[2021-10-29 17:36:56] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:56] Done.
Validation 20, 2 remaining
[2021-10-29 17:36:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:57] Number of windows considered: 1...
[2021-10-29 17:36:57] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:58] Done.
Validation 21, 1 remaining
[2021-10-29 17:36:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:36:59] Number of windows considered: 1...
[2021-10-29 17:36:59] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:36:59] Done.
Validation 22, 0 remaining
[2021-10-29 17:37:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:00] Number of windows considered: 1...
[2021-10-29 17:37:00] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:37:00] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-10-29 17:37:01] Performing annual aggregation...
[2021-10-29 17:37:01] Done.
[2021-10-29 17:37:01] - Computing climatology...
[2021-10-29 17:37:01] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm2.cl5 <- index.cal.station.cl5
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
EQM-WT5 PQM-WT5 GPQM2-WT5 GPQM-WT5
0.7209280 0.5449431 0.3686923 0.3686378
scores.st6.wt5 <- scores
Complete period (WO WTs)
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
[2021-10-29 17:37:01] Performing annual aggregation...
[2021-10-29 17:37:02] Done.
[2021-10-29 17:37:02] - Computing climatology...
[2021-10-29 17:37:02] - Done.
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)
index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
[2021-10-29 17:37:02] Performing annual aggregation...
[2021-10-29 17:37:02] Done.
[2021-10-29 17:37:02] - Computing climatology...
[2021-10-29 17:37:02] - Done.
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "pqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-10-29 17:37:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:03] Number of windows considered: 1...
[2021-10-29 17:37:03] Bias-correcting 1 members separately...
[2021-10-29 17:37:03] Done.
Validation 2, 20 remaining
[2021-10-29 17:37:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:04] Number of windows considered: 1...
[2021-10-29 17:37:04] Bias-correcting 1 members separately...
[2021-10-29 17:37:04] Done.
Validation 3, 19 remaining
[2021-10-29 17:37:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:05] Number of windows considered: 1...
[2021-10-29 17:37:05] Bias-correcting 1 members separately...
[2021-10-29 17:37:06] Done.
Validation 4, 18 remaining
[2021-10-29 17:37:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:07] Number of windows considered: 1...
[2021-10-29 17:37:07] Bias-correcting 1 members separately...
[2021-10-29 17:37:07] Done.
Validation 5, 17 remaining
[2021-10-29 17:37:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:08] Number of windows considered: 1...
[2021-10-29 17:37:08] Bias-correcting 1 members separately...
[2021-10-29 17:37:08] Done.
Validation 6, 16 remaining
[2021-10-29 17:37:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:09] Number of windows considered: 1...
[2021-10-29 17:37:09] Bias-correcting 1 members separately...
[2021-10-29 17:37:09] Done.
Validation 7, 15 remaining
[2021-10-29 17:37:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:10] Number of windows considered: 1...
[2021-10-29 17:37:10] Bias-correcting 1 members separately...
[2021-10-29 17:37:11] Done.
Validation 8, 14 remaining
[2021-10-29 17:37:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:12] Number of windows considered: 1...
[2021-10-29 17:37:12] Bias-correcting 1 members separately...
[2021-10-29 17:37:12] Done.
Validation 9, 13 remaining
[2021-10-29 17:37:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:13] Number of windows considered: 1...
[2021-10-29 17:37:13] Bias-correcting 1 members separately...
[2021-10-29 17:37:13] Done.
Validation 10, 12 remaining
[2021-10-29 17:37:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:14] Number of windows considered: 1...
[2021-10-29 17:37:14] Bias-correcting 1 members separately...
[2021-10-29 17:37:14] Done.
Validation 11, 11 remaining
[2021-10-29 17:37:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:15] Number of windows considered: 1...
[2021-10-29 17:37:15] Bias-correcting 1 members separately...
[2021-10-29 17:37:15] Done.
Validation 12, 10 remaining
[2021-10-29 17:37:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:16] Number of windows considered: 1...
[2021-10-29 17:37:16] Bias-correcting 1 members separately...
[2021-10-29 17:37:16] Done.
Validation 13, 9 remaining
[2021-10-29 17:37:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:17] Number of windows considered: 1...
[2021-10-29 17:37:17] Bias-correcting 1 members separately...
[2021-10-29 17:37:17] Done.
Validation 14, 8 remaining
[2021-10-29 17:37:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:18] Number of windows considered: 1...
[2021-10-29 17:37:18] Bias-correcting 1 members separately...
[2021-10-29 17:37:18] Done.
Validation 15, 7 remaining
[2021-10-29 17:37:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:19] Number of windows considered: 1...
[2021-10-29 17:37:19] Bias-correcting 1 members separately...
[2021-10-29 17:37:19] Done.
Validation 16, 6 remaining
[2021-10-29 17:37:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:20] Number of windows considered: 1...
[2021-10-29 17:37:20] Bias-correcting 1 members separately...
[2021-10-29 17:37:20] Done.
Validation 17, 5 remaining
[2021-10-29 17:37:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:21] Number of windows considered: 1...
[2021-10-29 17:37:21] Bias-correcting 1 members separately...
[2021-10-29 17:37:21] Done.
Validation 18, 4 remaining
[2021-10-29 17:37:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:22] Number of windows considered: 1...
[2021-10-29 17:37:22] Bias-correcting 1 members separately...
[2021-10-29 17:37:22] Done.
Validation 19, 3 remaining
[2021-10-29 17:37:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:23] Number of windows considered: 1...
[2021-10-29 17:37:23] Bias-correcting 1 members separately...
[2021-10-29 17:37:23] Done.
Validation 20, 2 remaining
[2021-10-29 17:37:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:24] Number of windows considered: 1...
[2021-10-29 17:37:24] Bias-correcting 1 members separately...
[2021-10-29 17:37:24] Done.
Validation 21, 1 remaining
[2021-10-29 17:37:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:25] Number of windows considered: 1...
[2021-10-29 17:37:25] Bias-correcting 1 members separately...
[2021-10-29 17:37:25] Done.
Validation 22, 0 remaining
[2021-10-29 17:37:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:26] Number of windows considered: 1...
[2021-10-29 17:37:26] Bias-correcting 1 members separately...
[2021-10-29 17:37:26] Done.
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:37:27] Performing annual aggregation...
[2021-10-29 17:37:27] Done.
[2021-10-29 17:37:27] - Computing climatology...
[2021-10-29 17:37:27] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.pqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "eqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-10-29 17:37:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:28] Number of windows considered: 1...
[2021-10-29 17:37:28] Bias-correcting 1 members separately...
[2021-10-29 17:37:28] Done.
Validation 2, 20 remaining
[2021-10-29 17:37:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:29] Number of windows considered: 1...
[2021-10-29 17:37:29] Bias-correcting 1 members separately...
[2021-10-29 17:37:29] Done.
Validation 3, 19 remaining
[2021-10-29 17:37:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:30] Number of windows considered: 1...
[2021-10-29 17:37:30] Bias-correcting 1 members separately...
[2021-10-29 17:37:30] Done.
Validation 4, 18 remaining
[2021-10-29 17:37:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:31] Number of windows considered: 1...
[2021-10-29 17:37:31] Bias-correcting 1 members separately...
[2021-10-29 17:37:32] Done.
Validation 5, 17 remaining
[2021-10-29 17:37:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:33] Number of windows considered: 1...
[2021-10-29 17:37:33] Bias-correcting 1 members separately...
[2021-10-29 17:37:33] Done.
Validation 6, 16 remaining
[2021-10-29 17:37:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:34] Number of windows considered: 1...
[2021-10-29 17:37:34] Bias-correcting 1 members separately...
[2021-10-29 17:37:34] Done.
Validation 7, 15 remaining
[2021-10-29 17:37:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:35] Number of windows considered: 1...
[2021-10-29 17:37:35] Bias-correcting 1 members separately...
[2021-10-29 17:37:35] Done.
Validation 8, 14 remaining
[2021-10-29 17:37:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:36] Number of windows considered: 1...
[2021-10-29 17:37:36] Bias-correcting 1 members separately...
[2021-10-29 17:37:36] Done.
Validation 9, 13 remaining
[2021-10-29 17:37:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:37] Number of windows considered: 1...
[2021-10-29 17:37:37] Bias-correcting 1 members separately...
[2021-10-29 17:37:37] Done.
Validation 10, 12 remaining
[2021-10-29 17:37:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:39] Number of windows considered: 1...
[2021-10-29 17:37:39] Bias-correcting 1 members separately...
[2021-10-29 17:37:39] Done.
Validation 11, 11 remaining
[2021-10-29 17:37:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:40] Number of windows considered: 1...
[2021-10-29 17:37:40] Bias-correcting 1 members separately...
[2021-10-29 17:37:40] Done.
Validation 12, 10 remaining
[2021-10-29 17:37:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:41] Number of windows considered: 1...
[2021-10-29 17:37:41] Bias-correcting 1 members separately...
[2021-10-29 17:37:41] Done.
Validation 13, 9 remaining
[2021-10-29 17:37:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:42] Number of windows considered: 1...
[2021-10-29 17:37:42] Bias-correcting 1 members separately...
[2021-10-29 17:37:42] Done.
Validation 14, 8 remaining
[2021-10-29 17:37:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:43] Number of windows considered: 1...
[2021-10-29 17:37:43] Bias-correcting 1 members separately...
[2021-10-29 17:37:44] Done.
Validation 15, 7 remaining
[2021-10-29 17:37:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:44] Number of windows considered: 1...
[2021-10-29 17:37:44] Bias-correcting 1 members separately...
[2021-10-29 17:37:45] Done.
Validation 16, 6 remaining
[2021-10-29 17:37:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:46] Number of windows considered: 1...
[2021-10-29 17:37:46] Bias-correcting 1 members separately...
[2021-10-29 17:37:46] Done.
Validation 17, 5 remaining
[2021-10-29 17:37:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:47] Number of windows considered: 1...
[2021-10-29 17:37:47] Bias-correcting 1 members separately...
[2021-10-29 17:37:47] Done.
Validation 18, 4 remaining
[2021-10-29 17:37:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:48] Number of windows considered: 1...
[2021-10-29 17:37:48] Bias-correcting 1 members separately...
[2021-10-29 17:37:48] Done.
Validation 19, 3 remaining
[2021-10-29 17:37:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:49] Number of windows considered: 1...
[2021-10-29 17:37:49] Bias-correcting 1 members separately...
[2021-10-29 17:37:49] Done.
Validation 20, 2 remaining
[2021-10-29 17:37:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:50] Number of windows considered: 1...
[2021-10-29 17:37:50] Bias-correcting 1 members separately...
[2021-10-29 17:37:51] Done.
Validation 21, 1 remaining
[2021-10-29 17:37:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:52] Number of windows considered: 1...
[2021-10-29 17:37:52] Bias-correcting 1 members separately...
[2021-10-29 17:37:52] Done.
Validation 22, 0 remaining
[2021-10-29 17:37:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:53] Number of windows considered: 1...
[2021-10-29 17:37:53] Bias-correcting 1 members separately...
[2021-10-29 17:37:53] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:37:53] Performing annual aggregation...
[2021-10-29 17:37:53] Done.
[2021-10-29 17:37:53] - Computing climatology...
[2021-10-29 17:37:53] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.eqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", cross.val = "loo")
Validation 1, 21 remaining
[2021-10-29 17:37:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:55] Number of windows considered: 1...
[2021-10-29 17:37:55] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:37:55] Done.
Validation 2, 20 remaining
[2021-10-29 17:37:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:56] Number of windows considered: 1...
[2021-10-29 17:37:56] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:37:57] Done.
Validation 3, 19 remaining
[2021-10-29 17:37:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:58] Number of windows considered: 1...
[2021-10-29 17:37:58] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:37:58] Done.
Validation 4, 18 remaining
[2021-10-29 17:37:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:37:59] Number of windows considered: 1...
[2021-10-29 17:37:59] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:00] Done.
Validation 5, 17 remaining
[2021-10-29 17:38:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:01] Number of windows considered: 1...
[2021-10-29 17:38:01] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:01] Done.
Validation 6, 16 remaining
[2021-10-29 17:38:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:03] Number of windows considered: 1...
[2021-10-29 17:38:03] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:03] Done.
Validation 7, 15 remaining
[2021-10-29 17:38:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:04] Number of windows considered: 1...
[2021-10-29 17:38:04] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:05] Done.
Validation 8, 14 remaining
[2021-10-29 17:38:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:06] Number of windows considered: 1...
[2021-10-29 17:38:06] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:06] Done.
Validation 9, 13 remaining
[2021-10-29 17:38:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:08] Number of windows considered: 1...
[2021-10-29 17:38:08] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:08] Done.
Validation 10, 12 remaining
[2021-10-29 17:38:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:09] Number of windows considered: 1...
[2021-10-29 17:38:09] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:10] Done.
Validation 11, 11 remaining
[2021-10-29 17:38:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:11] Number of windows considered: 1...
[2021-10-29 17:38:11] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:11] Done.
Validation 12, 10 remaining
[2021-10-29 17:38:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:12] Number of windows considered: 1...
[2021-10-29 17:38:12] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:13] Done.
Validation 13, 9 remaining
[2021-10-29 17:38:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:14] Number of windows considered: 1...
[2021-10-29 17:38:14] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:14] Done.
Validation 14, 8 remaining
[2021-10-29 17:38:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:15] Number of windows considered: 1...
[2021-10-29 17:38:15] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:16] Done.
Validation 15, 7 remaining
[2021-10-29 17:38:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:17] Number of windows considered: 1...
[2021-10-29 17:38:17] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:18] Done.
Validation 16, 6 remaining
[2021-10-29 17:38:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:19] Number of windows considered: 1...
[2021-10-29 17:38:19] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:19] Done.
Validation 17, 5 remaining
[2021-10-29 17:38:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:20] Number of windows considered: 1...
[2021-10-29 17:38:20] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:21] Done.
Validation 18, 4 remaining
[2021-10-29 17:38:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:22] Number of windows considered: 1...
[2021-10-29 17:38:22] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:22] Done.
Validation 19, 3 remaining
[2021-10-29 17:38:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:23] Number of windows considered: 1...
[2021-10-29 17:38:23] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:24] Done.
Validation 20, 2 remaining
[2021-10-29 17:38:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:25] Number of windows considered: 1...
[2021-10-29 17:38:25] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:26] Done.
Validation 21, 1 remaining
[2021-10-29 17:38:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:27] Number of windows considered: 1...
[2021-10-29 17:38:27] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:27] Done.
Validation 22, 0 remaining
[2021-10-29 17:38:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:28] Number of windows considered: 1...
[2021-10-29 17:38:28] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:29] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:38:29] Performing annual aggregation...
[2021-10-29 17:38:29] Done.
[2021-10-29 17:38:29] - Computing climatology...
[2021-10-29 17:38:29] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", theta = .7, cross.val = "loo")
Validation 1, 21 remaining
[2021-10-29 17:38:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:31] Number of windows considered: 1...
[2021-10-29 17:38:31] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:31] Done.
Validation 2, 20 remaining
[2021-10-29 17:38:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:32] Number of windows considered: 1...
[2021-10-29 17:38:32] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:33] Done.
Validation 3, 19 remaining
[2021-10-29 17:38:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:34] Number of windows considered: 1...
[2021-10-29 17:38:34] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:34] Done.
Validation 4, 18 remaining
[2021-10-29 17:38:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:35] Number of windows considered: 1...
[2021-10-29 17:38:35] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:36] Done.
Validation 5, 17 remaining
[2021-10-29 17:38:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:37] Number of windows considered: 1...
[2021-10-29 17:38:37] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:37] Done.
Validation 6, 16 remaining
[2021-10-29 17:38:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:38] Number of windows considered: 1...
[2021-10-29 17:38:38] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:39] Done.
Validation 7, 15 remaining
[2021-10-29 17:38:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:40] Number of windows considered: 1...
[2021-10-29 17:38:40] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:40] Done.
Validation 8, 14 remaining
[2021-10-29 17:38:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:41] Number of windows considered: 1...
[2021-10-29 17:38:41] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:41] Done.
Validation 9, 13 remaining
[2021-10-29 17:38:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:42] Number of windows considered: 1...
[2021-10-29 17:38:42] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:43] Done.
Validation 10, 12 remaining
[2021-10-29 17:38:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:44] Number of windows considered: 1...
[2021-10-29 17:38:44] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:44] Done.
Validation 11, 11 remaining
[2021-10-29 17:38:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:45] Number of windows considered: 1...
[2021-10-29 17:38:45] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:46] Done.
Validation 12, 10 remaining
[2021-10-29 17:38:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:47] Number of windows considered: 1...
[2021-10-29 17:38:47] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:47] Done.
Validation 13, 9 remaining
[2021-10-29 17:38:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:48] Number of windows considered: 1...
[2021-10-29 17:38:48] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:48] Done.
Validation 14, 8 remaining
[2021-10-29 17:38:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:50] Number of windows considered: 1...
[2021-10-29 17:38:50] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:50] Done.
Validation 15, 7 remaining
[2021-10-29 17:38:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:51] Number of windows considered: 1...
[2021-10-29 17:38:51] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:52] Done.
Validation 16, 6 remaining
[2021-10-29 17:38:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:53] Number of windows considered: 1...
[2021-10-29 17:38:53] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:53] Done.
Validation 17, 5 remaining
[2021-10-29 17:38:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:54] Number of windows considered: 1...
[2021-10-29 17:38:54] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:55] Done.
Validation 18, 4 remaining
[2021-10-29 17:38:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:56] Number of windows considered: 1...
[2021-10-29 17:38:56] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:56] Done.
Validation 19, 3 remaining
[2021-10-29 17:38:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:57] Number of windows considered: 1...
[2021-10-29 17:38:57] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:58] Done.
Validation 20, 2 remaining
[2021-10-29 17:38:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:38:59] Number of windows considered: 1...
[2021-10-29 17:38:59] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:38:59] Done.
Validation 21, 1 remaining
[2021-10-29 17:39:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:00] Number of windows considered: 1...
[2021-10-29 17:39:00] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:01] Done.
Validation 22, 0 remaining
[2021-10-29 17:39:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:02] Number of windows considered: 1...
[2021-10-29 17:39:02] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:02] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:39:03] Performing annual aggregation...
[2021-10-29 17:39:03] Done.
[2021-10-29 17:39:03] - Computing climatology...
[2021-10-29 17:39:03] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm2.complete <- index.cal.station.complete
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.trmm.complete[i]-index.obs.complete[i]),abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
score.trmm <- c()
for (i in c(1:9)) {
score.trmm <- c(score.trmm, norm.vector[[i]][1])
}
score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][2])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][3])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][4])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][5])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
PQM-C GPQM2-C EQM-C GPQM-C TRMM
0.8660336 0.7853354 0.7149623 0.6189193 0.1152653
scores.complete <- scores
paste(names(scores.st6.wt1[1]),names(scores.st6.wt2[1]),names(scores.st6.wt3[1]),names(scores.st6.wt4[1]),names(scores.st6.wt5[1]), names(scores.complete[1]))
[1] "EQM-WT1 PQM-WT2 PQM-WT3 EQM-WT4 EQM-WT5 PQM-C"
Combination of techniques by WT
cal.station.cl1.gpqm2 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm", theta = .7, cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 17:39:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:05] Number of windows considered: 1...
[2021-10-29 17:39:05] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:05] Done.
Validation 2, 20 remaining
[2021-10-29 17:39:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:06] Number of windows considered: 1...
[2021-10-29 17:39:06] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:06] Done.
Validation 3, 19 remaining
[2021-10-29 17:39:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:07] Number of windows considered: 1...
[2021-10-29 17:39:07] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:07] Done.
Validation 4, 18 remaining
[2021-10-29 17:39:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:08] Number of windows considered: 1...
[2021-10-29 17:39:08] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:08] Done.
Validation 5, 17 remaining
[2021-10-29 17:39:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:10] Number of windows considered: 1...
[2021-10-29 17:39:10] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:10] Done.
Validation 6, 16 remaining
[2021-10-29 17:39:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:11] Number of windows considered: 1...
[2021-10-29 17:39:11] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:11] Done.
Validation 7, 15 remaining
[2021-10-29 17:39:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:12] Number of windows considered: 1...
[2021-10-29 17:39:12] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:12] Done.
Validation 8, 14 remaining
[2021-10-29 17:39:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:13] Number of windows considered: 1...
[2021-10-29 17:39:13] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:13] Done.
Validation 9, 13 remaining
[2021-10-29 17:39:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:14] Number of windows considered: 1...
[2021-10-29 17:39:14] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:14] Done.
Validation 10, 12 remaining
[2021-10-29 17:39:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:15] Number of windows considered: 1...
[2021-10-29 17:39:15] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:15] Done.
Validation 11, 11 remaining
[2021-10-29 17:39:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:16] Number of windows considered: 1...
[2021-10-29 17:39:16] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:16] Done.
Validation 12, 10 remaining
[2021-10-29 17:39:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:17] Number of windows considered: 1...
[2021-10-29 17:39:17] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:17] Done.
Validation 13, 9 remaining
[2021-10-29 17:39:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:18] Number of windows considered: 1...
[2021-10-29 17:39:18] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:18] Done.
Validation 14, 8 remaining
[2021-10-29 17:39:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:19] Number of windows considered: 1...
[2021-10-29 17:39:19] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:19] Done.
Validation 15, 7 remaining
[2021-10-29 17:39:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:20] Number of windows considered: 1...
[2021-10-29 17:39:20] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:20] Done.
Validation 16, 6 remaining
[2021-10-29 17:39:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:21] Number of windows considered: 1...
[2021-10-29 17:39:21] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:21] Done.
Validation 17, 5 remaining
[2021-10-29 17:39:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:22] Number of windows considered: 1...
[2021-10-29 17:39:22] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:22] Done.
Validation 18, 4 remaining
[2021-10-29 17:39:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:23] Number of windows considered: 1...
[2021-10-29 17:39:23] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:23] Done.
Validation 19, 3 remaining
[2021-10-29 17:39:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:24] Number of windows considered: 1...
[2021-10-29 17:39:24] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:24] Done.
Validation 20, 2 remaining
[2021-10-29 17:39:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:25] Number of windows considered: 1...
[2021-10-29 17:39:25] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:25] Done.
Validation 21, 1 remaining
[2021-10-29 17:39:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:26] Number of windows considered: 1...
[2021-10-29 17:39:26] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:26] Done.
Validation 22, 0 remaining
[2021-10-29 17:39:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:27] Number of windows considered: 1...
[2021-10-29 17:39:27] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs producedNaNs produced[2021-10-29 17:39:28] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl1.gpqm2$Dates$start <- as.POSIXct(cal.station.cl1.gpqm2$Dates$start,tz = "GMT")
cal.station.cl1.gpqm2$Dates$end <- as.POSIXct(cal.station.cl1.gpqm2$Dates$end,tz = "GMT")
cal.station.cl2.pqm <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "pqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 17:39:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:29] Number of windows considered: 1...
[2021-10-29 17:39:29] Bias-correcting 1 members separately...
[2021-10-29 17:39:29] Done.
Validation 2, 20 remaining
[2021-10-29 17:39:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:30] Number of windows considered: 1...
[2021-10-29 17:39:30] Bias-correcting 1 members separately...
[2021-10-29 17:39:30] Done.
Validation 3, 19 remaining
[2021-10-29 17:39:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:31] Number of windows considered: 1...
[2021-10-29 17:39:31] Bias-correcting 1 members separately...
[2021-10-29 17:39:31] Done.
Validation 4, 18 remaining
[2021-10-29 17:39:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:32] Number of windows considered: 1...
[2021-10-29 17:39:32] Bias-correcting 1 members separately...
[2021-10-29 17:39:32] Done.
Validation 5, 17 remaining
[2021-10-29 17:39:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:33] Number of windows considered: 1...
[2021-10-29 17:39:33] Bias-correcting 1 members separately...
[2021-10-29 17:39:33] Done.
Validation 6, 16 remaining
[2021-10-29 17:39:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:34] Number of windows considered: 1...
[2021-10-29 17:39:34] Bias-correcting 1 members separately...
[2021-10-29 17:39:34] Done.
Validation 7, 15 remaining
[2021-10-29 17:39:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:35] Number of windows considered: 1...
[2021-10-29 17:39:35] Bias-correcting 1 members separately...
[2021-10-29 17:39:35] Done.
Validation 8, 14 remaining
[2021-10-29 17:39:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:36] Number of windows considered: 1...
[2021-10-29 17:39:36] Bias-correcting 1 members separately...
[2021-10-29 17:39:36] Done.
Validation 9, 13 remaining
[2021-10-29 17:39:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:37] Number of windows considered: 1...
[2021-10-29 17:39:37] Bias-correcting 1 members separately...
[2021-10-29 17:39:37] Done.
Validation 10, 12 remaining
[2021-10-29 17:39:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:38] Number of windows considered: 1...
[2021-10-29 17:39:38] Bias-correcting 1 members separately...
[2021-10-29 17:39:39] Done.
Validation 11, 11 remaining
[2021-10-29 17:39:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:39] Number of windows considered: 1...
[2021-10-29 17:39:40] Bias-correcting 1 members separately...
[2021-10-29 17:39:40] Done.
Validation 12, 10 remaining
[2021-10-29 17:39:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:41] Number of windows considered: 1...
[2021-10-29 17:39:41] Bias-correcting 1 members separately...
[2021-10-29 17:39:41] Done.
Validation 13, 9 remaining
[2021-10-29 17:39:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:42] Number of windows considered: 1...
[2021-10-29 17:39:42] Bias-correcting 1 members separately...
[2021-10-29 17:39:42] Done.
Validation 14, 8 remaining
[2021-10-29 17:39:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:43] Number of windows considered: 1...
[2021-10-29 17:39:43] Bias-correcting 1 members separately...
[2021-10-29 17:39:43] Done.
Validation 15, 7 remaining
[2021-10-29 17:39:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:44] Number of windows considered: 1...
[2021-10-29 17:39:44] Bias-correcting 1 members separately...
[2021-10-29 17:39:44] Done.
Validation 16, 6 remaining
[2021-10-29 17:39:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:45] Number of windows considered: 1...
[2021-10-29 17:39:45] Bias-correcting 1 members separately...
[2021-10-29 17:39:45] Done.
Validation 17, 5 remaining
[2021-10-29 17:39:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:46] Number of windows considered: 1...
[2021-10-29 17:39:46] Bias-correcting 1 members separately...
[2021-10-29 17:39:46] Done.
Validation 18, 4 remaining
[2021-10-29 17:39:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:47] Number of windows considered: 1...
[2021-10-29 17:39:47] Bias-correcting 1 members separately...
[2021-10-29 17:39:47] Done.
Validation 19, 3 remaining
[2021-10-29 17:39:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:48] Number of windows considered: 1...
[2021-10-29 17:39:48] Bias-correcting 1 members separately...
[2021-10-29 17:39:48] Done.
Validation 20, 2 remaining
[2021-10-29 17:39:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:49] Number of windows considered: 1...
[2021-10-29 17:39:49] Bias-correcting 1 members separately...
[2021-10-29 17:39:49] Done.
Validation 21, 1 remaining
[2021-10-29 17:39:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:50] Number of windows considered: 1...
[2021-10-29 17:39:50] Bias-correcting 1 members separately...
[2021-10-29 17:39:51] Done.
Validation 22, 0 remaining
[2021-10-29 17:39:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:52] Number of windows considered: 1...
[2021-10-29 17:39:52] Bias-correcting 1 members separately...
[2021-10-29 17:39:52] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl2.pqm$Dates$start <- as.POSIXct(cal.station.cl2.pqm$Dates$start,tz = "GMT")
cal.station.cl2.pqm$Dates$end <- as.POSIXct(cal.station.cl2.pqm$Dates$end,tz = "GMT")
cal.station.cl3.pqm <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "pqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 17:39:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:53] Number of windows considered: 1...
[2021-10-29 17:39:53] Bias-correcting 1 members separately...
[2021-10-29 17:39:53] Done.
Validation 2, 20 remaining
[2021-10-29 17:39:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:54] Number of windows considered: 1...
[2021-10-29 17:39:54] Bias-correcting 1 members separately...
[2021-10-29 17:39:55] Done.
Validation 3, 19 remaining
[2021-10-29 17:39:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:56] Number of windows considered: 1...
[2021-10-29 17:39:56] Bias-correcting 1 members separately...
[2021-10-29 17:39:56] Done.
Validation 4, 18 remaining
[2021-10-29 17:39:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:57] Number of windows considered: 1...
[2021-10-29 17:39:57] Bias-correcting 1 members separately...
[2021-10-29 17:39:57] Done.
Validation 5, 17 remaining
[2021-10-29 17:39:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:58] Number of windows considered: 1...
[2021-10-29 17:39:58] Bias-correcting 1 members separately...
[2021-10-29 17:39:58] Done.
Validation 6, 16 remaining
[2021-10-29 17:39:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:39:59] Number of windows considered: 1...
[2021-10-29 17:39:59] Bias-correcting 1 members separately...
[2021-10-29 17:39:59] Done.
Validation 7, 15 remaining
[2021-10-29 17:40:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:00] Number of windows considered: 1...
[2021-10-29 17:40:00] Bias-correcting 1 members separately...
[2021-10-29 17:40:00] Done.
Validation 8, 14 remaining
[2021-10-29 17:40:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:01] Number of windows considered: 1...
[2021-10-29 17:40:01] Bias-correcting 1 members separately...
[2021-10-29 17:40:01] Done.
Validation 9, 13 remaining
[2021-10-29 17:40:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:02] Number of windows considered: 1...
[2021-10-29 17:40:02] Bias-correcting 1 members separately...
[2021-10-29 17:40:02] Done.
Validation 10, 12 remaining
[2021-10-29 17:40:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:03] Number of windows considered: 1...
[2021-10-29 17:40:03] Bias-correcting 1 members separately...
[2021-10-29 17:40:04] Done.
Validation 11, 11 remaining
[2021-10-29 17:40:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:05] Number of windows considered: 1...
[2021-10-29 17:40:05] Bias-correcting 1 members separately...
[2021-10-29 17:40:05] Done.
Validation 12, 10 remaining
[2021-10-29 17:40:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:06] Number of windows considered: 1...
[2021-10-29 17:40:06] Bias-correcting 1 members separately...
[2021-10-29 17:40:06] Done.
Validation 13, 9 remaining
[2021-10-29 17:40:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:07] Number of windows considered: 1...
[2021-10-29 17:40:07] Bias-correcting 1 members separately...
[2021-10-29 17:40:07] Done.
Validation 14, 8 remaining
[2021-10-29 17:40:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:08] Number of windows considered: 1...
[2021-10-29 17:40:08] Bias-correcting 1 members separately...
[2021-10-29 17:40:08] Done.
Validation 15, 7 remaining
[2021-10-29 17:40:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:09] Number of windows considered: 1...
[2021-10-29 17:40:09] Bias-correcting 1 members separately...
[2021-10-29 17:40:09] Done.
Validation 16, 6 remaining
[2021-10-29 17:40:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:10] Number of windows considered: 1...
[2021-10-29 17:40:10] Bias-correcting 1 members separately...
[2021-10-29 17:40:11] Done.
Validation 17, 5 remaining
[2021-10-29 17:40:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:12] Number of windows considered: 1...
[2021-10-29 17:40:12] Bias-correcting 1 members separately...
[2021-10-29 17:40:12] Done.
Validation 18, 4 remaining
[2021-10-29 17:40:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:13] Number of windows considered: 1...
[2021-10-29 17:40:13] Bias-correcting 1 members separately...
[2021-10-29 17:40:13] Done.
Validation 19, 3 remaining
[2021-10-29 17:40:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:14] Number of windows considered: 1...
[2021-10-29 17:40:14] Bias-correcting 1 members separately...
[2021-10-29 17:40:14] Done.
Validation 20, 2 remaining
[2021-10-29 17:40:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:15] Number of windows considered: 1...
[2021-10-29 17:40:15] Bias-correcting 1 members separately...
[2021-10-29 17:40:15] Done.
Validation 21, 1 remaining
[2021-10-29 17:40:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:16] Number of windows considered: 1...
[2021-10-29 17:40:16] Bias-correcting 1 members separately...
[2021-10-29 17:40:17] Done.
Validation 22, 0 remaining
[2021-10-29 17:40:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:18] Number of windows considered: 1...
[2021-10-29 17:40:18] Bias-correcting 1 members separately...
[2021-10-29 17:40:18] Done.
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl3.pqm$Dates$start <- as.POSIXct(cal.station.cl3.pqm$Dates$start,tz = "GMT")
cal.station.cl3.pqm$Dates$end <- as.POSIXct(cal.station.cl3.pqm$Dates$end,tz = "GMT")
cal.station.cl4.eqm <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "eqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-10-29 17:40:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:19] Number of windows considered: 1...
[2021-10-29 17:40:19] Bias-correcting 1 members separately...
[2021-10-29 17:40:19] Done.
Validation 2, 20 remaining
[2021-10-29 17:40:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:20] Number of windows considered: 1...
[2021-10-29 17:40:20] Bias-correcting 1 members separately...
[2021-10-29 17:40:20] Done.
Validation 3, 19 remaining
[2021-10-29 17:40:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:22] Number of windows considered: 1...
[2021-10-29 17:40:22] Bias-correcting 1 members separately...
[2021-10-29 17:40:22] Done.
Validation 4, 18 remaining
[2021-10-29 17:40:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:23] Number of windows considered: 1...
[2021-10-29 17:40:23] Bias-correcting 1 members separately...
[2021-10-29 17:40:23] Done.
Validation 5, 17 remaining
[2021-10-29 17:40:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:24] Number of windows considered: 1...
[2021-10-29 17:40:24] Bias-correcting 1 members separately...
[2021-10-29 17:40:24] Done.
Validation 6, 16 remaining
[2021-10-29 17:40:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:26] Number of windows considered: 1...
[2021-10-29 17:40:26] Bias-correcting 1 members separately...
[2021-10-29 17:40:26] Done.
Validation 7, 15 remaining
[2021-10-29 17:40:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:27] Number of windows considered: 1...
[2021-10-29 17:40:27] Bias-correcting 1 members separately...
[2021-10-29 17:40:27] Done.
Validation 8, 14 remaining
[2021-10-29 17:40:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:28] Number of windows considered: 1...
[2021-10-29 17:40:28] Bias-correcting 1 members separately...
[2021-10-29 17:40:28] Done.
Validation 9, 13 remaining
[2021-10-29 17:40:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:29] Number of windows considered: 1...
[2021-10-29 17:40:29] Bias-correcting 1 members separately...
[2021-10-29 17:40:30] Done.
Validation 10, 12 remaining
[2021-10-29 17:40:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:31] Number of windows considered: 1...
[2021-10-29 17:40:31] Bias-correcting 1 members separately...
[2021-10-29 17:40:31] Done.
Validation 11, 11 remaining
[2021-10-29 17:40:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:32] Number of windows considered: 1...
[2021-10-29 17:40:32] Bias-correcting 1 members separately...
[2021-10-29 17:40:32] Done.
Validation 12, 10 remaining
[2021-10-29 17:40:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:33] Number of windows considered: 1...
[2021-10-29 17:40:33] Bias-correcting 1 members separately...
[2021-10-29 17:40:34] Done.
Validation 13, 9 remaining
[2021-10-29 17:40:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:35] Number of windows considered: 1...
[2021-10-29 17:40:35] Bias-correcting 1 members separately...
[2021-10-29 17:40:35] Done.
Validation 14, 8 remaining
[2021-10-29 17:40:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:36] Number of windows considered: 1...
[2021-10-29 17:40:36] Bias-correcting 1 members separately...
[2021-10-29 17:40:36] Done.
Validation 15, 7 remaining
[2021-10-29 17:40:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:37] Number of windows considered: 1...
[2021-10-29 17:40:37] Bias-correcting 1 members separately...
[2021-10-29 17:40:38] Done.
Validation 16, 6 remaining
[2021-10-29 17:40:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:39] Number of windows considered: 1...
[2021-10-29 17:40:39] Bias-correcting 1 members separately...
[2021-10-29 17:40:39] Done.
Validation 17, 5 remaining
[2021-10-29 17:40:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:40] Number of windows considered: 1...
[2021-10-29 17:40:40] Bias-correcting 1 members separately...
[2021-10-29 17:40:40] Done.
Validation 18, 4 remaining
[2021-10-29 17:40:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:41] Number of windows considered: 1...
[2021-10-29 17:40:41] Bias-correcting 1 members separately...
[2021-10-29 17:40:42] Done.
Validation 19, 3 remaining
[2021-10-29 17:40:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:43] Number of windows considered: 1...
[2021-10-29 17:40:43] Bias-correcting 1 members separately...
[2021-10-29 17:40:43] Done.
Validation 20, 2 remaining
[2021-10-29 17:40:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:44] Number of windows considered: 1...
[2021-10-29 17:40:44] Bias-correcting 1 members separately...
[2021-10-29 17:40:44] Done.
Validation 21, 1 remaining
[2021-10-29 17:40:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:45] Number of windows considered: 1...
[2021-10-29 17:40:45] Bias-correcting 1 members separately...
[2021-10-29 17:40:46] Done.
Validation 22, 0 remaining
[2021-10-29 17:40:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:47] Number of windows considered: 1...
[2021-10-29 17:40:47] Bias-correcting 1 members separately...
[2021-10-29 17:40:47] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl4.eqm$Dates$start <- as.POSIXct(cal.station.cl4.eqm$Dates$start,tz = "GMT")
cal.station.cl4.eqm$Dates$end <- as.POSIXct(cal.station.cl4.eqm$Dates$end,tz = "GMT")
cal.station.cl5.pqm <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-10-29 17:40:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:49] Number of windows considered: 1...
[2021-10-29 17:40:49] Bias-correcting 1 members separately...
[2021-10-29 17:40:49] Done.
Validation 2, 20 remaining
[2021-10-29 17:40:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:50] Number of windows considered: 1...
[2021-10-29 17:40:50] Bias-correcting 1 members separately...
[2021-10-29 17:40:50] Done.
Validation 3, 19 remaining
[2021-10-29 17:40:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:51] Number of windows considered: 1...
[2021-10-29 17:40:51] Bias-correcting 1 members separately...
[2021-10-29 17:40:51] Done.
Validation 4, 18 remaining
[2021-10-29 17:40:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:52] Number of windows considered: 1...
[2021-10-29 17:40:52] Bias-correcting 1 members separately...
[2021-10-29 17:40:52] Done.
Validation 5, 17 remaining
[2021-10-29 17:40:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:53] Number of windows considered: 1...
[2021-10-29 17:40:53] Bias-correcting 1 members separately...
[2021-10-29 17:40:53] Done.
Validation 6, 16 remaining
[2021-10-29 17:40:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:54] Number of windows considered: 1...
[2021-10-29 17:40:54] Bias-correcting 1 members separately...
[2021-10-29 17:40:54] Done.
Validation 7, 15 remaining
[2021-10-29 17:40:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:55] Number of windows considered: 1...
[2021-10-29 17:40:55] Bias-correcting 1 members separately...
[2021-10-29 17:40:55] Done.
Validation 8, 14 remaining
[2021-10-29 17:40:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:56] Number of windows considered: 1...
[2021-10-29 17:40:56] Bias-correcting 1 members separately...
[2021-10-29 17:40:56] Done.
Validation 9, 13 remaining
[2021-10-29 17:40:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:57] Number of windows considered: 1...
[2021-10-29 17:40:57] Bias-correcting 1 members separately...
[2021-10-29 17:40:57] Done.
Validation 10, 12 remaining
[2021-10-29 17:40:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:58] Number of windows considered: 1...
[2021-10-29 17:40:58] Bias-correcting 1 members separately...
[2021-10-29 17:40:58] Done.
Validation 11, 11 remaining
[2021-10-29 17:40:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:40:59] Number of windows considered: 1...
[2021-10-29 17:40:59] Bias-correcting 1 members separately...
[2021-10-29 17:40:59] Done.
Validation 12, 10 remaining
[2021-10-29 17:41:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:00] Number of windows considered: 1...
[2021-10-29 17:41:00] Bias-correcting 1 members separately...
[2021-10-29 17:41:00] Done.
Validation 13, 9 remaining
[2021-10-29 17:41:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:01] Number of windows considered: 1...
[2021-10-29 17:41:01] Bias-correcting 1 members separately...
[2021-10-29 17:41:01] Done.
Validation 14, 8 remaining
[2021-10-29 17:41:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:02] Number of windows considered: 1...
[2021-10-29 17:41:02] Bias-correcting 1 members separately...
[2021-10-29 17:41:02] Done.
Validation 15, 7 remaining
[2021-10-29 17:41:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:02] Number of windows considered: 1...
[2021-10-29 17:41:02] Bias-correcting 1 members separately...
[2021-10-29 17:41:03] Done.
Validation 16, 6 remaining
[2021-10-29 17:41:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:04] Number of windows considered: 1...
[2021-10-29 17:41:04] Bias-correcting 1 members separately...
[2021-10-29 17:41:04] Done.
Validation 17, 5 remaining
[2021-10-29 17:41:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:05] Number of windows considered: 1...
[2021-10-29 17:41:05] Bias-correcting 1 members separately...
[2021-10-29 17:41:05] Done.
Validation 18, 4 remaining
[2021-10-29 17:41:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:06] Number of windows considered: 1...
[2021-10-29 17:41:06] Bias-correcting 1 members separately...
[2021-10-29 17:41:06] Done.
Validation 19, 3 remaining
[2021-10-29 17:41:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:07] Number of windows considered: 1...
[2021-10-29 17:41:07] Bias-correcting 1 members separately...
[2021-10-29 17:41:07] Done.
Validation 20, 2 remaining
[2021-10-29 17:41:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:08] Number of windows considered: 1...
[2021-10-29 17:41:08] Bias-correcting 1 members separately...
[2021-10-29 17:41:08] Done.
Validation 21, 1 remaining
[2021-10-29 17:41:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:09] Number of windows considered: 1...
[2021-10-29 17:41:09] Bias-correcting 1 members separately...
[2021-10-29 17:41:09] Done.
Validation 22, 0 remaining
[2021-10-29 17:41:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:10] Number of windows considered: 1...
[2021-10-29 17:41:10] Bias-correcting 1 members separately...
[2021-10-29 17:41:10] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl5.pqm$Dates$start <- as.POSIXct(cal.station.cl5.pqm$Dates$start,tz = "GMT")
cal.station.cl5.pqm$Dates$end <- as.POSIXct(cal.station.cl5.pqm$Dates$end,tz = "GMT")
cal.station.cl5.pqm$Dates$start <- as.POSIXct(cal.station.cl5.pqm$Dates$start,tz = "GMT")
cal.station.cl5.pqm$Dates$end <- as.POSIXct(cal.station.cl5.pqm$Dates$end,tz = "GMT")
idx <- which(!is.na(cal.station.cl1.gpqm2$Data))
cal.station.cl1.gpqm2 <- subsetDimension(cal.station.cl1.gpqm2, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl2.pqm$Data))
cal.station.cl2.pqm <- subsetDimension(cal.station.cl2.pqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl3.pqm$Data))
cal.station.cl3.pqm <- subsetDimension(cal.station.cl3.pqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl4.eqm$Data))
cal.station.cl4.eqm <- subsetDimension(cal.station.cl4.eqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl5.pqm$Data))
cal.station.cl5.pqm <- subsetDimension(cal.station.cl5.pqm, dimension = "time", indices = idx)
wt_conditioned <- bindGrid(cal.station.cl1.gpqm2, cal.station.cl2.pqm, cal.station.cl3.pqm,
cal.station.cl4.eqm, cal.station.cl5.pqm, dimension = "time")
attr(wt_conditioned$Data, "dimensions") <- "time"
#cambiar de tipo de biasCorrection y fillGridDates
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "pqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-10-29 17:41:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:12] Number of windows considered: 1...
[2021-10-29 17:41:12] Bias-correcting 1 members separately...
[2021-10-29 17:41:12] Done.
Validation 2, 20 remaining
[2021-10-29 17:41:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:13] Number of windows considered: 1...
[2021-10-29 17:41:13] Bias-correcting 1 members separately...
[2021-10-29 17:41:13] Done.
Validation 3, 19 remaining
[2021-10-29 17:41:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:14] Number of windows considered: 1...
[2021-10-29 17:41:14] Bias-correcting 1 members separately...
[2021-10-29 17:41:14] Done.
Validation 4, 18 remaining
[2021-10-29 17:41:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:15] Number of windows considered: 1...
[2021-10-29 17:41:15] Bias-correcting 1 members separately...
[2021-10-29 17:41:15] Done.
Validation 5, 17 remaining
[2021-10-29 17:41:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:16] Number of windows considered: 1...
[2021-10-29 17:41:16] Bias-correcting 1 members separately...
[2021-10-29 17:41:16] Done.
Validation 6, 16 remaining
[2021-10-29 17:41:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:17] Number of windows considered: 1...
[2021-10-29 17:41:17] Bias-correcting 1 members separately...
[2021-10-29 17:41:17] Done.
Validation 7, 15 remaining
[2021-10-29 17:41:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:18] Number of windows considered: 1...
[2021-10-29 17:41:18] Bias-correcting 1 members separately...
[2021-10-29 17:41:19] Done.
Validation 8, 14 remaining
[2021-10-29 17:41:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:20] Number of windows considered: 1...
[2021-10-29 17:41:20] Bias-correcting 1 members separately...
[2021-10-29 17:41:20] Done.
Validation 9, 13 remaining
[2021-10-29 17:41:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:21] Number of windows considered: 1...
[2021-10-29 17:41:21] Bias-correcting 1 members separately...
[2021-10-29 17:41:21] Done.
Validation 10, 12 remaining
[2021-10-29 17:41:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:22] Number of windows considered: 1...
[2021-10-29 17:41:22] Bias-correcting 1 members separately...
[2021-10-29 17:41:22] Done.
Validation 11, 11 remaining
[2021-10-29 17:41:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:23] Number of windows considered: 1...
[2021-10-29 17:41:23] Bias-correcting 1 members separately...
[2021-10-29 17:41:23] Done.
Validation 12, 10 remaining
[2021-10-29 17:41:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:24] Number of windows considered: 1...
[2021-10-29 17:41:24] Bias-correcting 1 members separately...
[2021-10-29 17:41:24] Done.
Validation 13, 9 remaining
[2021-10-29 17:41:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:25] Number of windows considered: 1...
[2021-10-29 17:41:25] Bias-correcting 1 members separately...
[2021-10-29 17:41:25] Done.
Validation 14, 8 remaining
[2021-10-29 17:41:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:26] Number of windows considered: 1...
[2021-10-29 17:41:26] Bias-correcting 1 members separately...
[2021-10-29 17:41:26] Done.
Validation 15, 7 remaining
[2021-10-29 17:41:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:28] Number of windows considered: 1...
[2021-10-29 17:41:28] Bias-correcting 1 members separately...
[2021-10-29 17:41:28] Done.
Validation 16, 6 remaining
[2021-10-29 17:41:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:29] Number of windows considered: 1...
[2021-10-29 17:41:29] Bias-correcting 1 members separately...
[2021-10-29 17:41:29] Done.
Validation 17, 5 remaining
[2021-10-29 17:41:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:30] Number of windows considered: 1...
[2021-10-29 17:41:30] Bias-correcting 1 members separately...
[2021-10-29 17:41:30] Done.
Validation 18, 4 remaining
[2021-10-29 17:41:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:31] Number of windows considered: 1...
[2021-10-29 17:41:31] Bias-correcting 1 members separately...
[2021-10-29 17:41:31] Done.
Validation 19, 3 remaining
[2021-10-29 17:41:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:32] Number of windows considered: 1...
[2021-10-29 17:41:32] Bias-correcting 1 members separately...
[2021-10-29 17:41:32] Done.
Validation 20, 2 remaining
[2021-10-29 17:41:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:33] Number of windows considered: 1...
[2021-10-29 17:41:33] Bias-correcting 1 members separately...
[2021-10-29 17:41:33] Done.
Validation 21, 1 remaining
[2021-10-29 17:41:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:34] Number of windows considered: 1...
[2021-10-29 17:41:34] Bias-correcting 1 members separately...
[2021-10-29 17:41:34] Done.
Validation 22, 0 remaining
[2021-10-29 17:41:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-10-29 17:41:36] Number of windows considered: 1...
[2021-10-29 17:41:36] Bias-correcting 1 members separately...
[2021-10-29 17:41:36] Done.
# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))
index.combinated.rv20max <- MaxReturnValue(wt_conditioned)
[2021-10-29 17:41:36] Performing annual aggregation...
[2021-10-29 17:41:36] Done.
[2021-10-29 17:41:36] - Computing climatology...
[2021-10-29 17:41:36] - Done.
index.combinated <- c(index.combinated, index.combinated.rv20max)
index.pqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.pqm <- c(index.pqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.pqm.rv20max <- MaxReturnValue(cal.station.complete)
[2021-10-29 17:41:37] Performing annual aggregation...
[2021-10-29 17:41:37] Done.
[2021-10-29 17:41:37] - Computing climatology...
[2021-10-29 17:41:37] - Done.
index.pqm<- c(index.pqm ,index.pqm.rv20max)
index.pqm
Skewness SDII R10 R10p R20 R20p P98Wet
3.803757e+00 2.139479e+01 3.066965e-01 9.326624e+04 1.889470e-01 7.994351e+04 1.158034e+02
P98WetAmount RV20_max
1.584166e+04 2.573763e+02
diff.conditioned <- abs(index.obs-index.combinated)
diff.pqm <- abs(index.obs-index.pqm)
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
score.combinated <- c()
for (i in c(1:9)) {
score.combinated <- c(score.combinated, norm.vector[[i]][5])
}
score.combinated <- mean(score.combinated)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
Combined PQM-C GPQM2-C EQM-C GPQM-C
0.7541450 0.7202412 0.5561347 0.4403908 0.2485875
df <- data.frame(index.obs, index.combinated, index.cal.station.pqm.complete)
colnames(df) <- c("Observation","Conditioned", "PQM")
format(df, digits = 3, scientific = 5)
bias.df <- data.frame(diff.conditioned, diff.pqm)
colnames(bias.df) <- c("Bias Conditioned", "Bias PQM")
format(bias.df, digits = 3, scientific = 5)
df.st1 <- df
bias.df.st1 <- bias.df
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100
names(bias.rel.cond) <- names(diff.conditioned)
bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100
names(bias.rel.no.cond) <- names(diff.conditioned)
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)
colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias PQM")
format(bias.rel.df, digits = 3, scientific = 5)
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))
abline(a = 0, b = 1)
station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))
points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))
idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))
station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)
points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)
legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))
grid()

Nu’uuli, American Samoa
i=7
There were 21 warnings (use warnings() to see them)
station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
[2021-11-02 11:19:24] Performing annual aggregation...
[2021-11-02 11:19:24] Done.
[2021-11-02 11:19:24] - Computing climatology...
[2021-11-02 11:19:24] - Done.
index.obs <- c(index.obs, index.obs.rv20max)
index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
[2021-11-02 11:19:25] Performing annual aggregation...
[2021-11-02 11:19:25] Done.
[2021-11-02 11:19:25] - Computing climatology...
[2021-11-02 11:19:25] - Done.
index.trmm <- c(index.trmm, index.trmm.rv20max)
WT1
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))
station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
[2021-11-02 11:19:31] Performing annual aggregation...
[2021-11-02 11:19:31] Done.
[2021-11-02 11:19:31] - Computing climatology...
[2021-11-02 11:19:31] - Done.
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)
index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
[2021-11-02 11:19:31] Performing annual aggregation...
[2021-11-02 11:19:31] Done.
[2021-11-02 11:19:31] - Computing climatology...
[2021-11-02 11:19:31] - Done.
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")
station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "pqm",cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:19:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:36] Number of windows considered: 1...
[2021-11-02 11:19:36] Bias-correcting 1 members separately...
[2021-11-02 11:19:36] Done.
Validation 2, 20 remaining
[2021-11-02 11:19:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:37] Number of windows considered: 1...
[2021-11-02 11:19:37] Bias-correcting 1 members separately...
[2021-11-02 11:19:37] Done.
Validation 3, 19 remaining
[2021-11-02 11:19:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:38] Number of windows considered: 1...
[2021-11-02 11:19:38] Bias-correcting 1 members separately...
[2021-11-02 11:19:38] Done.
Validation 4, 18 remaining
[2021-11-02 11:19:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:39] Number of windows considered: 1...
[2021-11-02 11:19:39] Bias-correcting 1 members separately...
[2021-11-02 11:19:39] Done.
Validation 5, 17 remaining
[2021-11-02 11:19:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:40] Number of windows considered: 1...
[2021-11-02 11:19:40] Bias-correcting 1 members separately...
[2021-11-02 11:19:40] Done.
Validation 6, 16 remaining
[2021-11-02 11:19:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:42] Number of windows considered: 1...
[2021-11-02 11:19:42] Bias-correcting 1 members separately...
[2021-11-02 11:19:42] Done.
Validation 7, 15 remaining
[2021-11-02 11:19:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:43] Number of windows considered: 1...
[2021-11-02 11:19:43] Bias-correcting 1 members separately...
[2021-11-02 11:19:43] Done.
Validation 8, 14 remaining
[2021-11-02 11:19:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:44] Number of windows considered: 1...
[2021-11-02 11:19:44] Bias-correcting 1 members separately...
[2021-11-02 11:19:44] Done.
Validation 9, 13 remaining
[2021-11-02 11:19:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:45] Number of windows considered: 1...
[2021-11-02 11:19:45] Bias-correcting 1 members separately...
[2021-11-02 11:19:45] Done.
Validation 10, 12 remaining
[2021-11-02 11:19:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:46] Number of windows considered: 1...
[2021-11-02 11:19:46] Bias-correcting 1 members separately...
[2021-11-02 11:19:46] Done.
Validation 11, 11 remaining
[2021-11-02 11:19:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:47] Number of windows considered: 1...
[2021-11-02 11:19:47] Bias-correcting 1 members separately...
[2021-11-02 11:19:47] Done.
Validation 12, 10 remaining
[2021-11-02 11:19:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:48] Number of windows considered: 1...
[2021-11-02 11:19:48] Bias-correcting 1 members separately...
[2021-11-02 11:19:48] Done.
Validation 13, 9 remaining
[2021-11-02 11:19:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:49] Number of windows considered: 1...
[2021-11-02 11:19:49] Bias-correcting 1 members separately...
[2021-11-02 11:19:49] Done.
Validation 14, 8 remaining
[2021-11-02 11:19:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:50] Number of windows considered: 1...
[2021-11-02 11:19:50] Bias-correcting 1 members separately...
[2021-11-02 11:19:50] Done.
Validation 15, 7 remaining
[2021-11-02 11:19:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:51] Number of windows considered: 1...
[2021-11-02 11:19:51] Bias-correcting 1 members separately...
[2021-11-02 11:19:51] Done.
Validation 16, 6 remaining
[2021-11-02 11:19:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:52] Number of windows considered: 1...
[2021-11-02 11:19:52] Bias-correcting 1 members separately...
[2021-11-02 11:19:52] Done.
Validation 17, 5 remaining
[2021-11-02 11:19:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:53] Number of windows considered: 1...
[2021-11-02 11:19:53] Bias-correcting 1 members separately...
[2021-11-02 11:19:53] Done.
Validation 18, 4 remaining
[2021-11-02 11:19:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:54] Number of windows considered: 1...
[2021-11-02 11:19:54] Bias-correcting 1 members separately...
[2021-11-02 11:19:54] Done.
Validation 19, 3 remaining
[2021-11-02 11:19:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:55] Number of windows considered: 1...
[2021-11-02 11:19:55] Bias-correcting 1 members separately...
[2021-11-02 11:19:55] Done.
Validation 20, 2 remaining
[2021-11-02 11:19:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:56] Number of windows considered: 1...
[2021-11-02 11:19:56] Bias-correcting 1 members separately...
[2021-11-02 11:19:56] Done.
Validation 21, 1 remaining
[2021-11-02 11:19:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:57] Number of windows considered: 1...
[2021-11-02 11:19:57] Bias-correcting 1 members separately...
[2021-11-02 11:19:57] Done.
Validation 22, 0 remaining
[2021-11-02 11:19:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:19:58] Number of windows considered: 1...
[2021-11-02 11:19:58] Bias-correcting 1 members separately...
[2021-11-02 11:19:58] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-11-02 11:19:58] Performing annual aggregation...
[2021-11-02 11:19:58] Done.
[2021-11-02 11:19:58] - Computing climatology...
[2021-11-02 11:19:58] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.pqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:22:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:14] Number of windows considered: 1...
[2021-11-02 11:22:14] Bias-correcting 1 members separately...
[2021-11-02 11:22:14] Done.
Validation 2, 20 remaining
[2021-11-02 11:22:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:15] Number of windows considered: 1...
[2021-11-02 11:22:15] Bias-correcting 1 members separately...
[2021-11-02 11:22:15] Done.
Validation 3, 19 remaining
[2021-11-02 11:22:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:16] Number of windows considered: 1...
[2021-11-02 11:22:16] Bias-correcting 1 members separately...
[2021-11-02 11:22:17] Done.
Validation 4, 18 remaining
[2021-11-02 11:22:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:18] Number of windows considered: 1...
[2021-11-02 11:22:18] Bias-correcting 1 members separately...
[2021-11-02 11:22:18] Done.
Validation 5, 17 remaining
[2021-11-02 11:22:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:19] Number of windows considered: 1...
[2021-11-02 11:22:19] Bias-correcting 1 members separately...
[2021-11-02 11:22:19] Done.
Validation 6, 16 remaining
[2021-11-02 11:22:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:20] Number of windows considered: 1...
[2021-11-02 11:22:20] Bias-correcting 1 members separately...
[2021-11-02 11:22:20] Done.
Validation 7, 15 remaining
[2021-11-02 11:22:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:21] Number of windows considered: 1...
[2021-11-02 11:22:21] Bias-correcting 1 members separately...
[2021-11-02 11:22:21] Done.
Validation 8, 14 remaining
[2021-11-02 11:22:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:23] Number of windows considered: 1...
[2021-11-02 11:22:23] Bias-correcting 1 members separately...
[2021-11-02 11:22:23] Done.
Validation 9, 13 remaining
[2021-11-02 11:22:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:24] Number of windows considered: 1...
[2021-11-02 11:22:24] Bias-correcting 1 members separately...
[2021-11-02 11:22:24] Done.
Validation 10, 12 remaining
[2021-11-02 11:22:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:25] Number of windows considered: 1...
[2021-11-02 11:22:25] Bias-correcting 1 members separately...
[2021-11-02 11:22:25] Done.
Validation 11, 11 remaining
[2021-11-02 11:22:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:26] Number of windows considered: 1...
[2021-11-02 11:22:26] Bias-correcting 1 members separately...
[2021-11-02 11:22:26] Done.
Validation 12, 10 remaining
[2021-11-02 11:22:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:27] Number of windows considered: 1...
[2021-11-02 11:22:27] Bias-correcting 1 members separately...
[2021-11-02 11:22:27] Done.
Validation 13, 9 remaining
[2021-11-02 11:22:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:28] Number of windows considered: 1...
[2021-11-02 11:22:28] Bias-correcting 1 members separately...
[2021-11-02 11:22:28] Done.
Validation 14, 8 remaining
[2021-11-02 11:22:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:29] Number of windows considered: 1...
[2021-11-02 11:22:29] Bias-correcting 1 members separately...
[2021-11-02 11:22:29] Done.
Validation 15, 7 remaining
[2021-11-02 11:22:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:30] Number of windows considered: 1...
[2021-11-02 11:22:30] Bias-correcting 1 members separately...
[2021-11-02 11:22:30] Done.
Validation 16, 6 remaining
[2021-11-02 11:22:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:31] Number of windows considered: 1...
[2021-11-02 11:22:31] Bias-correcting 1 members separately...
[2021-11-02 11:22:31] Done.
Validation 17, 5 remaining
[2021-11-02 11:22:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:32] Number of windows considered: 1...
[2021-11-02 11:22:32] Bias-correcting 1 members separately...
[2021-11-02 11:22:32] Done.
Validation 18, 4 remaining
[2021-11-02 11:22:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:33] Number of windows considered: 1...
[2021-11-02 11:22:33] Bias-correcting 1 members separately...
[2021-11-02 11:22:33] Done.
Validation 19, 3 remaining
[2021-11-02 11:22:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:34] Number of windows considered: 1...
[2021-11-02 11:22:34] Bias-correcting 1 members separately...
[2021-11-02 11:22:34] Done.
Validation 20, 2 remaining
[2021-11-02 11:22:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:35] Number of windows considered: 1...
[2021-11-02 11:22:35] Bias-correcting 1 members separately...
[2021-11-02 11:22:35] Done.
Validation 21, 1 remaining
[2021-11-02 11:22:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:36] Number of windows considered: 1...
[2021-11-02 11:22:36] Bias-correcting 1 members separately...
[2021-11-02 11:22:36] Done.
Validation 22, 0 remaining
[2021-11-02 11:22:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:37] Number of windows considered: 1...
[2021-11-02 11:22:37] Bias-correcting 1 members separately...
[2021-11-02 11:22:37] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-11-02 11:22:38] Performing annual aggregation...
[2021-11-02 11:22:38] Done.
[2021-11-02 11:22:38] - Computing climatology...
[2021-11-02 11:22:38] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.eqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:22:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:39] Number of windows considered: 1...
[2021-11-02 11:22:39] Bias-correcting 1 members separately...
[2021-11-02 11:22:40] Done.
Validation 2, 20 remaining
[2021-11-02 11:22:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:41] Number of windows considered: 1...
[2021-11-02 11:22:41] Bias-correcting 1 members separately...
[2021-11-02 11:22:41] Done.
Validation 3, 19 remaining
[2021-11-02 11:22:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:42] Number of windows considered: 1...
[2021-11-02 11:22:42] Bias-correcting 1 members separately...
[2021-11-02 11:22:42] Done.
Validation 4, 18 remaining
[2021-11-02 11:22:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:43] Number of windows considered: 1...
[2021-11-02 11:22:43] Bias-correcting 1 members separately...
[2021-11-02 11:22:43] Done.
Validation 5, 17 remaining
[2021-11-02 11:22:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:44] Number of windows considered: 1...
[2021-11-02 11:22:44] Bias-correcting 1 members separately...
[2021-11-02 11:22:44] Done.
Validation 6, 16 remaining
[2021-11-02 11:22:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:45] Number of windows considered: 1...
[2021-11-02 11:22:45] Bias-correcting 1 members separately...
[2021-11-02 11:22:45] Done.
Validation 7, 15 remaining
[2021-11-02 11:22:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:46] Number of windows considered: 1...
[2021-11-02 11:22:46] Bias-correcting 1 members separately...
[2021-11-02 11:22:46] Done.
Validation 8, 14 remaining
[2021-11-02 11:22:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:47] Number of windows considered: 1...
[2021-11-02 11:22:47] Bias-correcting 1 members separately...
[2021-11-02 11:22:48] Done.
Validation 9, 13 remaining
[2021-11-02 11:22:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:49] Number of windows considered: 1...
[2021-11-02 11:22:49] Bias-correcting 1 members separately...
[2021-11-02 11:22:49] Done.
Validation 10, 12 remaining
[2021-11-02 11:22:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:50] Number of windows considered: 1...
[2021-11-02 11:22:50] Bias-correcting 1 members separately...
[2021-11-02 11:22:50] Done.
Validation 11, 11 remaining
[2021-11-02 11:22:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:51] Number of windows considered: 1...
[2021-11-02 11:22:51] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:22:51] Done.
Validation 12, 10 remaining
[2021-11-02 11:22:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:52] Number of windows considered: 1...
[2021-11-02 11:22:52] Bias-correcting 1 members separately...
[2021-11-02 11:22:52] Done.
Validation 13, 9 remaining
[2021-11-02 11:22:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:53] Number of windows considered: 1...
[2021-11-02 11:22:53] Bias-correcting 1 members separately...
[2021-11-02 11:22:53] Done.
Validation 14, 8 remaining
[2021-11-02 11:22:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:54] Number of windows considered: 1...
[2021-11-02 11:22:54] Bias-correcting 1 members separately...
[2021-11-02 11:22:54] Done.
Validation 15, 7 remaining
[2021-11-02 11:22:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:55] Number of windows considered: 1...
[2021-11-02 11:22:55] Bias-correcting 1 members separately...
[2021-11-02 11:22:55] Done.
Validation 16, 6 remaining
[2021-11-02 11:22:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:56] Number of windows considered: 1...
[2021-11-02 11:22:56] Bias-correcting 1 members separately...
[2021-11-02 11:22:56] Done.
Validation 17, 5 remaining
[2021-11-02 11:22:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:57] Number of windows considered: 1...
[2021-11-02 11:22:57] Bias-correcting 1 members separately...
[2021-11-02 11:22:57] Done.
Validation 18, 4 remaining
[2021-11-02 11:22:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:58] Number of windows considered: 1...
[2021-11-02 11:22:58] Bias-correcting 1 members separately...
[2021-11-02 11:22:58] Done.
Validation 19, 3 remaining
[2021-11-02 11:22:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:22:59] Number of windows considered: 1...
[2021-11-02 11:22:59] Bias-correcting 1 members separately...
[2021-11-02 11:22:59] Done.
Validation 20, 2 remaining
[2021-11-02 11:23:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:00] Number of windows considered: 1...
[2021-11-02 11:23:00] Bias-correcting 1 members separately...
[2021-11-02 11:23:00] Done.
Validation 21, 1 remaining
[2021-11-02 11:23:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:01] Number of windows considered: 1...
[2021-11-02 11:23:01] Bias-correcting 1 members separately...
[2021-11-02 11:23:01] Done.
Validation 22, 0 remaining
[2021-11-02 11:23:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:02] Number of windows considered: 1...
[2021-11-02 11:23:02] Bias-correcting 1 members separately...
[2021-11-02 11:23:02] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-11-02 11:23:02] Performing annual aggregation...
[2021-11-02 11:23:02] Done.
[2021-11-02 11:23:02] - Computing climatology...
[2021-11-02 11:23:02] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm.cl1 <- index.cal.station.cl1
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:23:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:04] Number of windows considered: 1...
[2021-11-02 11:23:04] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:04] Done.
Validation 2, 20 remaining
[2021-11-02 11:23:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:05] Number of windows considered: 1...
[2021-11-02 11:23:05] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:05] Done.
Validation 3, 19 remaining
[2021-11-02 11:23:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:06] Number of windows considered: 1...
[2021-11-02 11:23:06] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:06] Done.
Validation 4, 18 remaining
[2021-11-02 11:23:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:07] Number of windows considered: 1...
[2021-11-02 11:23:07] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:07] Done.
Validation 5, 17 remaining
[2021-11-02 11:23:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:08] Number of windows considered: 1...
[2021-11-02 11:23:08] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:08] Done.
Validation 6, 16 remaining
[2021-11-02 11:23:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:09] Number of windows considered: 1...
[2021-11-02 11:23:09] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:09] Done.
Validation 7, 15 remaining
[2021-11-02 11:23:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:10] Number of windows considered: 1...
[2021-11-02 11:23:10] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:10] Done.
Validation 8, 14 remaining
[2021-11-02 11:23:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:11] Number of windows considered: 1...
[2021-11-02 11:23:11] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:11] Done.
Validation 9, 13 remaining
[2021-11-02 11:23:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:12] Number of windows considered: 1...
[2021-11-02 11:23:12] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:12] Done.
Validation 10, 12 remaining
[2021-11-02 11:23:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:13] Number of windows considered: 1...
[2021-11-02 11:23:13] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:13] Done.
Validation 11, 11 remaining
[2021-11-02 11:23:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:14] Number of windows considered: 1...
[2021-11-02 11:23:14] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:14] Done.
Validation 12, 10 remaining
[2021-11-02 11:23:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:15] Number of windows considered: 1...
[2021-11-02 11:23:15] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:15] Done.
Validation 13, 9 remaining
[2021-11-02 11:23:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:16] Number of windows considered: 1...
[2021-11-02 11:23:16] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:16] Done.
Validation 14, 8 remaining
[2021-11-02 11:23:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:17] Number of windows considered: 1...
[2021-11-02 11:23:17] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:17] Done.
Validation 15, 7 remaining
[2021-11-02 11:23:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:18] Number of windows considered: 1...
[2021-11-02 11:23:18] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:18] Done.
Validation 16, 6 remaining
[2021-11-02 11:23:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:19] Number of windows considered: 1...
[2021-11-02 11:23:19] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:19] Done.
Validation 17, 5 remaining
[2021-11-02 11:23:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:20] Number of windows considered: 1...
[2021-11-02 11:23:20] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:20] Done.
Validation 18, 4 remaining
[2021-11-02 11:23:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:21] Number of windows considered: 1...
[2021-11-02 11:23:21] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:21] Done.
Validation 19, 3 remaining
[2021-11-02 11:23:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:22] Number of windows considered: 1...
[2021-11-02 11:23:22] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:22] Done.
Validation 20, 2 remaining
[2021-11-02 11:23:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:23] Number of windows considered: 1...
[2021-11-02 11:23:23] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:23] Done.
Validation 21, 1 remaining
[2021-11-02 11:23:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:24] Number of windows considered: 1...
[2021-11-02 11:23:24] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:24] Done.
Validation 22, 0 remaining
[2021-11-02 11:23:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:25] Number of windows considered: 1...
[2021-11-02 11:23:25] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:23:25] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))
cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")
index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)
[2021-11-02 11:23:26] Performing annual aggregation...
[2021-11-02 11:23:26] Done.
[2021-11-02 11:23:26] - Computing climatology...
[2021-11-02 11:23:26] - Done.
index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)
index.cal.station.gpqm2.cl1 <- index.cal.station.cl1
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i]))
}
normalization <- function(measure){
measure.norm <- c()
#measure must be a vector with the value of a certain measure of different calibrations
for (i in c(1:length(measure))) {
measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
}
return(measure.norm)
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
scores.st7.wt1 <- scores
WT2
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))
station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
[2021-11-02 11:23:27] Performing annual aggregation...
[2021-11-02 11:23:27] Done.
[2021-11-02 11:23:27] - Computing climatology...
[2021-11-02 11:23:27] - Done.
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)
index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
[2021-11-02 11:23:27] Performing annual aggregation...
[2021-11-02 11:23:27] Done.
[2021-11-02 11:23:27] - Computing climatology...
[2021-11-02 11:23:27] - Done.
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")
station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:23:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:29] Number of windows considered: 1...
[2021-11-02 11:23:29] Bias-correcting 1 members separately...
[2021-11-02 11:23:29] Done.
Validation 2, 20 remaining
[2021-11-02 11:23:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:30] Number of windows considered: 1...
[2021-11-02 11:23:30] Bias-correcting 1 members separately...
[2021-11-02 11:23:30] Done.
Validation 3, 19 remaining
[2021-11-02 11:23:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:31] Number of windows considered: 1...
[2021-11-02 11:23:31] Bias-correcting 1 members separately...
[2021-11-02 11:23:31] Done.
Validation 4, 18 remaining
[2021-11-02 11:23:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:32] Number of windows considered: 1...
[2021-11-02 11:23:32] Bias-correcting 1 members separately...
[2021-11-02 11:23:32] Done.
Validation 5, 17 remaining
[2021-11-02 11:23:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:33] Number of windows considered: 1...
[2021-11-02 11:23:33] Bias-correcting 1 members separately...
[2021-11-02 11:23:33] Done.
Validation 6, 16 remaining
[2021-11-02 11:23:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:34] Number of windows considered: 1...
[2021-11-02 11:23:34] Bias-correcting 1 members separately...
[2021-11-02 11:23:34] Done.
Validation 7, 15 remaining
[2021-11-02 11:23:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:35] Number of windows considered: 1...
[2021-11-02 11:23:35] Bias-correcting 1 members separately...
[2021-11-02 11:23:35] Done.
Validation 8, 14 remaining
[2021-11-02 11:23:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:36] Number of windows considered: 1...
[2021-11-02 11:23:36] Bias-correcting 1 members separately...
[2021-11-02 11:23:36] Done.
Validation 9, 13 remaining
[2021-11-02 11:23:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:37] Number of windows considered: 1...
[2021-11-02 11:23:37] Bias-correcting 1 members separately...
[2021-11-02 11:23:37] Done.
Validation 10, 12 remaining
[2021-11-02 11:23:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:38] Number of windows considered: 1...
[2021-11-02 11:23:38] Bias-correcting 1 members separately...
[2021-11-02 11:23:38] Done.
Validation 11, 11 remaining
[2021-11-02 11:23:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:39] Number of windows considered: 1...
[2021-11-02 11:23:39] Bias-correcting 1 members separately...
[2021-11-02 11:23:39] Done.
Validation 12, 10 remaining
[2021-11-02 11:23:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:40] Number of windows considered: 1...
[2021-11-02 11:23:40] Bias-correcting 1 members separately...
[2021-11-02 11:23:40] Done.
Validation 13, 9 remaining
[2021-11-02 11:23:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:41] Number of windows considered: 1...
[2021-11-02 11:23:41] Bias-correcting 1 members separately...
[2021-11-02 11:23:41] Done.
Validation 14, 8 remaining
[2021-11-02 11:23:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:42] Number of windows considered: 1...
[2021-11-02 11:23:42] Bias-correcting 1 members separately...
[2021-11-02 11:23:42] Done.
Validation 15, 7 remaining
[2021-11-02 11:23:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:43] Number of windows considered: 1...
[2021-11-02 11:23:43] Bias-correcting 1 members separately...
[2021-11-02 11:23:43] Done.
Validation 16, 6 remaining
[2021-11-02 11:23:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:44] Number of windows considered: 1...
[2021-11-02 11:23:44] Bias-correcting 1 members separately...
[2021-11-02 11:23:44] Done.
Validation 17, 5 remaining
[2021-11-02 11:23:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:45] Number of windows considered: 1...
[2021-11-02 11:23:45] Bias-correcting 1 members separately...
[2021-11-02 11:23:45] Done.
Validation 18, 4 remaining
[2021-11-02 11:23:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:46] Number of windows considered: 1...
[2021-11-02 11:23:46] Bias-correcting 1 members separately...
[2021-11-02 11:23:46] Done.
Validation 19, 3 remaining
[2021-11-02 11:23:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:47] Number of windows considered: 1...
[2021-11-02 11:23:47] Bias-correcting 1 members separately...
[2021-11-02 11:23:47] Done.
Validation 20, 2 remaining
[2021-11-02 11:23:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:48] Number of windows considered: 1...
[2021-11-02 11:23:48] Bias-correcting 1 members separately...
[2021-11-02 11:23:48] Done.
Validation 21, 1 remaining
[2021-11-02 11:23:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:49] Number of windows considered: 1...
[2021-11-02 11:23:49] Bias-correcting 1 members separately...
[2021-11-02 11:23:49] Done.
Validation 22, 0 remaining
[2021-11-02 11:23:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:50] Number of windows considered: 1...
[2021-11-02 11:23:50] Bias-correcting 1 members separately...
[2021-11-02 11:23:50] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-11-02 11:23:51] Performing annual aggregation...
[2021-11-02 11:23:51] Done.
[2021-11-02 11:23:51] - Computing climatology...
[2021-11-02 11:23:51] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.pqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:23:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:52] Number of windows considered: 1...
[2021-11-02 11:23:52] Bias-correcting 1 members separately...
[2021-11-02 11:23:52] Done.
Validation 2, 20 remaining
[2021-11-02 11:23:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:53] Number of windows considered: 1...
[2021-11-02 11:23:53] Bias-correcting 1 members separately...
[2021-11-02 11:23:53] Done.
Validation 3, 19 remaining
[2021-11-02 11:23:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:54] Number of windows considered: 1...
[2021-11-02 11:23:54] Bias-correcting 1 members separately...
[2021-11-02 11:23:54] Done.
Validation 4, 18 remaining
[2021-11-02 11:23:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:55] Number of windows considered: 1...
[2021-11-02 11:23:55] Bias-correcting 1 members separately...
[2021-11-02 11:23:56] Done.
Validation 5, 17 remaining
[2021-11-02 11:23:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:57] Number of windows considered: 1...
[2021-11-02 11:23:57] Bias-correcting 1 members separately...
[2021-11-02 11:23:57] Done.
Validation 6, 16 remaining
[2021-11-02 11:23:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:58] Number of windows considered: 1...
[2021-11-02 11:23:58] Bias-correcting 1 members separately...
[2021-11-02 11:23:58] Done.
Validation 7, 15 remaining
[2021-11-02 11:23:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:23:59] Number of windows considered: 1...
[2021-11-02 11:23:59] Bias-correcting 1 members separately...
[2021-11-02 11:23:59] Done.
Validation 8, 14 remaining
[2021-11-02 11:24:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:00] Number of windows considered: 1...
[2021-11-02 11:24:00] Bias-correcting 1 members separately...
[2021-11-02 11:24:00] Done.
Validation 9, 13 remaining
[2021-11-02 11:24:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:01] Number of windows considered: 1...
[2021-11-02 11:24:01] Bias-correcting 1 members separately...
[2021-11-02 11:24:01] Done.
Validation 10, 12 remaining
[2021-11-02 11:24:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:03] Number of windows considered: 1...
[2021-11-02 11:24:03] Bias-correcting 1 members separately...
[2021-11-02 11:24:03] Done.
Validation 11, 11 remaining
[2021-11-02 11:24:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:04] Number of windows considered: 1...
[2021-11-02 11:24:04] Bias-correcting 1 members separately...
[2021-11-02 11:24:04] Done.
Validation 12, 10 remaining
[2021-11-02 11:24:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:05] Number of windows considered: 1...
[2021-11-02 11:24:05] Bias-correcting 1 members separately...
[2021-11-02 11:24:05] Done.
Validation 13, 9 remaining
[2021-11-02 11:24:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:06] Number of windows considered: 1...
[2021-11-02 11:24:06] Bias-correcting 1 members separately...
[2021-11-02 11:24:06] Done.
Validation 14, 8 remaining
[2021-11-02 11:24:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:07] Number of windows considered: 1...
[2021-11-02 11:24:07] Bias-correcting 1 members separately...
[2021-11-02 11:24:07] Done.
Validation 15, 7 remaining
[2021-11-02 11:24:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:08] Number of windows considered: 1...
[2021-11-02 11:24:08] Bias-correcting 1 members separately...
[2021-11-02 11:24:09] Done.
Validation 16, 6 remaining
[2021-11-02 11:24:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:10] Number of windows considered: 1...
[2021-11-02 11:24:10] Bias-correcting 1 members separately...
[2021-11-02 11:24:10] Done.
Validation 17, 5 remaining
[2021-11-02 11:24:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:11] Number of windows considered: 1...
[2021-11-02 11:24:11] Bias-correcting 1 members separately...
[2021-11-02 11:24:11] Done.
Validation 18, 4 remaining
[2021-11-02 11:24:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:12] Number of windows considered: 1...
[2021-11-02 11:24:12] Bias-correcting 1 members separately...
[2021-11-02 11:24:12] Done.
Validation 19, 3 remaining
[2021-11-02 11:24:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:13] Number of windows considered: 1...
[2021-11-02 11:24:13] Bias-correcting 1 members separately...
[2021-11-02 11:24:13] Done.
Validation 20, 2 remaining
[2021-11-02 11:24:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:14] Number of windows considered: 1...
[2021-11-02 11:24:14] Bias-correcting 1 members separately...
[2021-11-02 11:24:14] Done.
Validation 21, 1 remaining
[2021-11-02 11:24:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:15] Number of windows considered: 1...
[2021-11-02 11:24:15] Bias-correcting 1 members separately...
[2021-11-02 11:24:15] Done.
Validation 22, 0 remaining
[2021-11-02 11:24:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:16] Number of windows considered: 1...
[2021-11-02 11:24:16] Bias-correcting 1 members separately...
[2021-11-02 11:24:17] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-11-02 11:24:17] Performing annual aggregation...
[2021-11-02 11:24:17] Done.
[2021-11-02 11:24:17] - Computing climatology...
[2021-11-02 11:24:17] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.eqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:24:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:19] Number of windows considered: 1...
[2021-11-02 11:24:19] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:24:19] Done.
Validation 2, 20 remaining
[2021-11-02 11:24:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:20] Number of windows considered: 1...
[2021-11-02 11:24:20] Bias-correcting 1 members separately...
[2021-11-02 11:24:20] Done.
Validation 3, 19 remaining
[2021-11-02 11:24:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:21] Number of windows considered: 1...
[2021-11-02 11:24:21] Bias-correcting 1 members separately...
[2021-11-02 11:24:21] Done.
Validation 4, 18 remaining
[2021-11-02 11:24:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:22] Number of windows considered: 1...
[2021-11-02 11:24:22] Bias-correcting 1 members separately...
[2021-11-02 11:24:22] Done.
Validation 5, 17 remaining
[2021-11-02 11:24:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:23] Number of windows considered: 1...
[2021-11-02 11:24:23] Bias-correcting 1 members separately...
[2021-11-02 11:24:23] Done.
Validation 6, 16 remaining
[2021-11-02 11:24:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:24] Number of windows considered: 1...
[2021-11-02 11:24:24] Bias-correcting 1 members separately...
[2021-11-02 11:24:25] Done.
Validation 7, 15 remaining
[2021-11-02 11:24:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:26] Number of windows considered: 1...
[2021-11-02 11:24:26] Bias-correcting 1 members separately...
[2021-11-02 11:24:26] Done.
Validation 8, 14 remaining
[2021-11-02 11:24:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:27] Number of windows considered: 1...
[2021-11-02 11:24:27] Bias-correcting 1 members separately...
[2021-11-02 11:24:27] Done.
Validation 9, 13 remaining
[2021-11-02 11:24:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:28] Number of windows considered: 1...
[2021-11-02 11:24:28] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:24:28] Done.
Validation 10, 12 remaining
[2021-11-02 11:24:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:29] Number of windows considered: 1...
[2021-11-02 11:24:29] Bias-correcting 1 members separately...
[2021-11-02 11:24:29] Done.
Validation 11, 11 remaining
[2021-11-02 11:24:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:30] Number of windows considered: 1...
[2021-11-02 11:24:30] Bias-correcting 1 members separately...
[2021-11-02 11:24:30] Done.
Validation 12, 10 remaining
[2021-11-02 11:24:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:31] Number of windows considered: 1...
[2021-11-02 11:24:31] Bias-correcting 1 members separately...
[2021-11-02 11:24:31] Done.
Validation 13, 9 remaining
[2021-11-02 11:24:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:32] Number of windows considered: 1...
[2021-11-02 11:24:32] Bias-correcting 1 members separately...
[2021-11-02 11:24:32] Done.
Validation 14, 8 remaining
[2021-11-02 11:24:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:33] Number of windows considered: 1...
[2021-11-02 11:24:33] Bias-correcting 1 members separately...
[2021-11-02 11:24:34] Done.
Validation 15, 7 remaining
[2021-11-02 11:24:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:35] Number of windows considered: 1...
[2021-11-02 11:24:35] Bias-correcting 1 members separately...
[2021-11-02 11:24:35] Done.
Validation 16, 6 remaining
[2021-11-02 11:24:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:36] Number of windows considered: 1...
[2021-11-02 11:24:36] Bias-correcting 1 members separately...
[2021-11-02 11:24:36] Done.
Validation 17, 5 remaining
[2021-11-02 11:24:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:38] Number of windows considered: 1...
[2021-11-02 11:24:38] Bias-correcting 1 members separately...
[2021-11-02 11:24:38] Done.
Validation 18, 4 remaining
[2021-11-02 11:24:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:40] Number of windows considered: 1...
[2021-11-02 11:24:40] Bias-correcting 1 members separately...
[2021-11-02 11:24:40] Done.
Validation 19, 3 remaining
[2021-11-02 11:24:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:42] Number of windows considered: 1...
[2021-11-02 11:24:42] Bias-correcting 1 members separately...
[2021-11-02 11:24:42] Done.
Validation 20, 2 remaining
[2021-11-02 11:24:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:43] Number of windows considered: 1...
[2021-11-02 11:24:43] Bias-correcting 1 members separately...
[2021-11-02 11:24:43] Done.
Validation 21, 1 remaining
[2021-11-02 11:24:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:44] Number of windows considered: 1...
[2021-11-02 11:24:44] Bias-correcting 1 members separately...
[2021-11-02 11:24:44] Done.
Validation 22, 0 remaining
[2021-11-02 11:24:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:45] Number of windows considered: 1...
[2021-11-02 11:24:45] Bias-correcting 1 members separately...
[2021-11-02 11:24:45] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-11-02 11:24:46] Performing annual aggregation...
[2021-11-02 11:24:46] Done.
[2021-11-02 11:24:46] - Computing climatology...
[2021-11-02 11:24:46] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm.cl2 <- index.cal.station.cl2
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:24:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:47] Number of windows considered: 1...
[2021-11-02 11:24:47] Bias-correcting 1 members separately...
[2021-11-02 11:24:47] Done.
Validation 2, 20 remaining
[2021-11-02 11:24:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:48] Number of windows considered: 1...
[2021-11-02 11:24:48] Bias-correcting 1 members separately...
[2021-11-02 11:24:48] Done.
Validation 3, 19 remaining
[2021-11-02 11:24:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:49] Number of windows considered: 1...
[2021-11-02 11:24:49] Bias-correcting 1 members separately...
[2021-11-02 11:24:50] Done.
Validation 4, 18 remaining
[2021-11-02 11:24:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:51] Number of windows considered: 1...
[2021-11-02 11:24:51] Bias-correcting 1 members separately...
[2021-11-02 11:24:51] Done.
Validation 5, 17 remaining
[2021-11-02 11:24:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:52] Number of windows considered: 1...
[2021-11-02 11:24:52] Bias-correcting 1 members separately...
[2021-11-02 11:24:52] Done.
Validation 6, 16 remaining
[2021-11-02 11:24:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:53] Number of windows considered: 1...
[2021-11-02 11:24:53] Bias-correcting 1 members separately...
[2021-11-02 11:24:53] Done.
Validation 7, 15 remaining
[2021-11-02 11:24:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:54] Number of windows considered: 1...
[2021-11-02 11:24:54] Bias-correcting 1 members separately...
[2021-11-02 11:24:54] Done.
Validation 8, 14 remaining
[2021-11-02 11:24:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:55] Number of windows considered: 1...
[2021-11-02 11:24:55] Bias-correcting 1 members separately...
[2021-11-02 11:24:55] Done.
Validation 9, 13 remaining
[2021-11-02 11:24:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:56] Number of windows considered: 1...
[2021-11-02 11:24:56] Bias-correcting 1 members separately...
[2021-11-02 11:24:57] Done.
Validation 10, 12 remaining
[2021-11-02 11:24:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:57] Number of windows considered: 1...
[2021-11-02 11:24:57] Bias-correcting 1 members separately...
[2021-11-02 11:24:58] Done.
Validation 11, 11 remaining
[2021-11-02 11:24:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:24:59] Number of windows considered: 1...
[2021-11-02 11:24:59] Bias-correcting 1 members separately...
[2021-11-02 11:24:59] Done.
Validation 12, 10 remaining
[2021-11-02 11:25:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:00] Number of windows considered: 1...
[2021-11-02 11:25:00] Bias-correcting 1 members separately...
[2021-11-02 11:25:00] Done.
Validation 13, 9 remaining
[2021-11-02 11:25:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:01] Number of windows considered: 1...
[2021-11-02 11:25:01] Bias-correcting 1 members separately...
[2021-11-02 11:25:01] Done.
Validation 14, 8 remaining
[2021-11-02 11:25:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:02] Number of windows considered: 1...
[2021-11-02 11:25:02] Bias-correcting 1 members separately...
[2021-11-02 11:25:02] Done.
Validation 15, 7 remaining
[2021-11-02 11:25:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:03] Number of windows considered: 1...
[2021-11-02 11:25:03] Bias-correcting 1 members separately...
[2021-11-02 11:25:03] Done.
Validation 16, 6 remaining
[2021-11-02 11:25:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:04] Number of windows considered: 1...
[2021-11-02 11:25:04] Bias-correcting 1 members separately...
[2021-11-02 11:25:04] Done.
Validation 17, 5 remaining
[2021-11-02 11:25:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:05] Number of windows considered: 1...
[2021-11-02 11:25:05] Bias-correcting 1 members separately...
[2021-11-02 11:25:06] Done.
Validation 18, 4 remaining
[2021-11-02 11:25:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:07] Number of windows considered: 1...
[2021-11-02 11:25:07] Bias-correcting 1 members separately...
[2021-11-02 11:25:07] Done.
Validation 19, 3 remaining
[2021-11-02 11:25:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:08] Number of windows considered: 1...
[2021-11-02 11:25:08] Bias-correcting 1 members separately...
[2021-11-02 11:25:08] Done.
Validation 20, 2 remaining
[2021-11-02 11:25:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:09] Number of windows considered: 1...
[2021-11-02 11:25:09] Bias-correcting 1 members separately...
[2021-11-02 11:25:09] Done.
Validation 21, 1 remaining
[2021-11-02 11:25:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:10] Number of windows considered: 1...
[2021-11-02 11:25:10] Bias-correcting 1 members separately...
[2021-11-02 11:25:10] Done.
Validation 22, 0 remaining
[2021-11-02 11:25:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:11] Number of windows considered: 1...
[2021-11-02 11:25:11] Bias-correcting 1 members separately...
[2021-11-02 11:25:11] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))
cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")
index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)
[2021-11-02 11:25:12] Performing annual aggregation...
[2021-11-02 11:25:12] Done.
[2021-11-02 11:25:12] - Computing climatology...
[2021-11-02 11:25:12] - Done.
index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)
index.cal.station.gpqm2.cl2 <- index.cal.station.cl2
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores
EQM-WT2 GPQM-WT2 PQM-WT2 GPQM2-WT2
0.7334727 0.6668888 0.5588170 0.2388523
scores.st7.wt2 <- scores
WT3
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))
station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
[2021-11-02 11:25:13] Performing annual aggregation...
[2021-11-02 11:25:13] Done.
[2021-11-02 11:25:13] - Computing climatology...
[2021-11-02 11:25:13] - Done.
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)
index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
[2021-11-02 11:25:13] Performing annual aggregation...
[2021-11-02 11:25:13] Done.
[2021-11-02 11:25:13] - Computing climatology...
[2021-11-02 11:25:13] - Done.
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")
station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:25:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:15] Number of windows considered: 1...
[2021-11-02 11:25:15] Bias-correcting 1 members separately...
[2021-11-02 11:25:15] Done.
Validation 2, 20 remaining
[2021-11-02 11:25:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:16] Number of windows considered: 1...
[2021-11-02 11:25:16] Bias-correcting 1 members separately...
[2021-11-02 11:25:16] Done.
Validation 3, 19 remaining
[2021-11-02 11:25:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:17] Number of windows considered: 1...
[2021-11-02 11:25:17] Bias-correcting 1 members separately...
[2021-11-02 11:25:17] Done.
Validation 4, 18 remaining
[2021-11-02 11:25:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:18] Number of windows considered: 1...
[2021-11-02 11:25:18] Bias-correcting 1 members separately...
[2021-11-02 11:25:18] Done.
Validation 5, 17 remaining
[2021-11-02 11:25:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:19] Number of windows considered: 1...
[2021-11-02 11:25:19] Bias-correcting 1 members separately...
[2021-11-02 11:25:19] Done.
Validation 6, 16 remaining
[2021-11-02 11:25:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:20] Number of windows considered: 1...
[2021-11-02 11:25:20] Bias-correcting 1 members separately...
[2021-11-02 11:25:20] Done.
Validation 7, 15 remaining
[2021-11-02 11:25:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:22] Number of windows considered: 1...
[2021-11-02 11:25:22] Bias-correcting 1 members separately...
[2021-11-02 11:25:22] Done.
Validation 8, 14 remaining
[2021-11-02 11:25:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:23] Number of windows considered: 1...
[2021-11-02 11:25:23] Bias-correcting 1 members separately...
[2021-11-02 11:25:23] Done.
Validation 9, 13 remaining
[2021-11-02 11:25:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:24] Number of windows considered: 1...
[2021-11-02 11:25:24] Bias-correcting 1 members separately...
[2021-11-02 11:25:24] Done.
Validation 10, 12 remaining
[2021-11-02 11:25:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:25] Number of windows considered: 1...
[2021-11-02 11:25:25] Bias-correcting 1 members separately...
[2021-11-02 11:25:25] Done.
Validation 11, 11 remaining
[2021-11-02 11:25:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:26] Number of windows considered: 1...
[2021-11-02 11:25:26] Bias-correcting 1 members separately...
[2021-11-02 11:25:27] Done.
Validation 12, 10 remaining
[2021-11-02 11:25:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:28] Number of windows considered: 1...
[2021-11-02 11:25:28] Bias-correcting 1 members separately...
[2021-11-02 11:25:28] Done.
Validation 13, 9 remaining
[2021-11-02 11:25:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:29] Number of windows considered: 1...
[2021-11-02 11:25:29] Bias-correcting 1 members separately...
[2021-11-02 11:25:29] Done.
Validation 14, 8 remaining
[2021-11-02 11:25:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:30] Number of windows considered: 1...
[2021-11-02 11:25:30] Bias-correcting 1 members separately...
[2021-11-02 11:25:30] Done.
Validation 15, 7 remaining
[2021-11-02 11:25:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:31] Number of windows considered: 1...
[2021-11-02 11:25:31] Bias-correcting 1 members separately...
[2021-11-02 11:25:31] Done.
Validation 16, 6 remaining
[2021-11-02 11:25:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:32] Number of windows considered: 1...
[2021-11-02 11:25:32] Bias-correcting 1 members separately...
[2021-11-02 11:25:33] Done.
Validation 17, 5 remaining
[2021-11-02 11:25:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:34] Number of windows considered: 1...
[2021-11-02 11:25:34] Bias-correcting 1 members separately...
[2021-11-02 11:25:34] Done.
Validation 18, 4 remaining
[2021-11-02 11:25:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:35] Number of windows considered: 1...
[2021-11-02 11:25:35] Bias-correcting 1 members separately...
[2021-11-02 11:25:35] Done.
Validation 19, 3 remaining
[2021-11-02 11:25:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:36] Number of windows considered: 1...
[2021-11-02 11:25:36] Bias-correcting 1 members separately...
[2021-11-02 11:25:36] Done.
Validation 20, 2 remaining
[2021-11-02 11:25:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:37] Number of windows considered: 1...
[2021-11-02 11:25:37] Bias-correcting 1 members separately...
[2021-11-02 11:25:37] Done.
Validation 21, 1 remaining
[2021-11-02 11:25:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:39] Number of windows considered: 1...
[2021-11-02 11:25:39] Bias-correcting 1 members separately...
[2021-11-02 11:25:39] Done.
Validation 22, 0 remaining
[2021-11-02 11:25:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:40] Number of windows considered: 1...
[2021-11-02 11:25:40] Bias-correcting 1 members separately...
[2021-11-02 11:25:40] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-11-02 11:25:40] Performing annual aggregation...
[2021-11-02 11:25:40] Done.
[2021-11-02 11:25:40] - Computing climatology...
[2021-11-02 11:25:40] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.pqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:25:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:41] Number of windows considered: 1...
[2021-11-02 11:25:41] Bias-correcting 1 members separately...
[2021-11-02 11:25:42] Done.
Validation 2, 20 remaining
[2021-11-02 11:25:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:43] Number of windows considered: 1...
[2021-11-02 11:25:43] Bias-correcting 1 members separately...
[2021-11-02 11:25:43] Done.
Validation 3, 19 remaining
[2021-11-02 11:25:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:44] Number of windows considered: 1...
[2021-11-02 11:25:44] Bias-correcting 1 members separately...
[2021-11-02 11:25:44] Done.
Validation 4, 18 remaining
[2021-11-02 11:25:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:45] Number of windows considered: 1...
[2021-11-02 11:25:45] Bias-correcting 1 members separately...
[2021-11-02 11:25:45] Done.
Validation 5, 17 remaining
[2021-11-02 11:25:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:47] Number of windows considered: 1...
[2021-11-02 11:25:47] Bias-correcting 1 members separately...
[2021-11-02 11:25:47] Done.
Validation 6, 16 remaining
[2021-11-02 11:25:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:48] Number of windows considered: 1...
[2021-11-02 11:25:48] Bias-correcting 1 members separately...
[2021-11-02 11:25:48] Done.
Validation 7, 15 remaining
[2021-11-02 11:25:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:49] Number of windows considered: 1...
[2021-11-02 11:25:49] Bias-correcting 1 members separately...
[2021-11-02 11:25:49] Done.
Validation 8, 14 remaining
[2021-11-02 11:25:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:51] Number of windows considered: 1...
[2021-11-02 11:25:51] Bias-correcting 1 members separately...
[2021-11-02 11:25:51] Done.
Validation 9, 13 remaining
[2021-11-02 11:25:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:52] Number of windows considered: 1...
[2021-11-02 11:25:52] Bias-correcting 1 members separately...
[2021-11-02 11:25:52] Done.
Validation 10, 12 remaining
[2021-11-02 11:25:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:53] Number of windows considered: 1...
[2021-11-02 11:25:53] Bias-correcting 1 members separately...
[2021-11-02 11:25:53] Done.
Validation 11, 11 remaining
[2021-11-02 11:25:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:55] Number of windows considered: 1...
[2021-11-02 11:25:55] Bias-correcting 1 members separately...
[2021-11-02 11:25:55] Done.
Validation 12, 10 remaining
[2021-11-02 11:25:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:56] Number of windows considered: 1...
[2021-11-02 11:25:56] Bias-correcting 1 members separately...
[2021-11-02 11:25:56] Done.
Validation 13, 9 remaining
[2021-11-02 11:25:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:57] Number of windows considered: 1...
[2021-11-02 11:25:57] Bias-correcting 1 members separately...
[2021-11-02 11:25:57] Done.
Validation 14, 8 remaining
[2021-11-02 11:25:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:25:59] Number of windows considered: 1...
[2021-11-02 11:25:59] Bias-correcting 1 members separately...
[2021-11-02 11:25:59] Done.
Validation 15, 7 remaining
[2021-11-02 11:26:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:00] Number of windows considered: 1...
[2021-11-02 11:26:00] Bias-correcting 1 members separately...
[2021-11-02 11:26:00] Done.
Validation 16, 6 remaining
[2021-11-02 11:26:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:02] Number of windows considered: 1...
[2021-11-02 11:26:02] Bias-correcting 1 members separately...
[2021-11-02 11:26:02] Done.
Validation 17, 5 remaining
[2021-11-02 11:26:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:03] Number of windows considered: 1...
[2021-11-02 11:26:03] Bias-correcting 1 members separately...
[2021-11-02 11:26:03] Done.
Validation 18, 4 remaining
[2021-11-02 11:26:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:05] Number of windows considered: 1...
[2021-11-02 11:26:05] Bias-correcting 1 members separately...
[2021-11-02 11:26:05] Done.
Validation 19, 3 remaining
[2021-11-02 11:26:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:06] Number of windows considered: 1...
[2021-11-02 11:26:06] Bias-correcting 1 members separately...
[2021-11-02 11:26:06] Done.
Validation 20, 2 remaining
[2021-11-02 11:26:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:07] Number of windows considered: 1...
[2021-11-02 11:26:07] Bias-correcting 1 members separately...
[2021-11-02 11:26:07] Done.
Validation 21, 1 remaining
[2021-11-02 11:26:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:09] Number of windows considered: 1...
[2021-11-02 11:26:09] Bias-correcting 1 members separately...
[2021-11-02 11:26:09] Done.
Validation 22, 0 remaining
[2021-11-02 11:26:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:11] Number of windows considered: 1...
[2021-11-02 11:26:11] Bias-correcting 1 members separately...
[2021-11-02 11:26:11] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-11-02 11:26:11] Performing annual aggregation...
[2021-11-02 11:26:11] Done.
[2021-11-02 11:26:11] - Computing climatology...
[2021-11-02 11:26:11] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.eqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:26:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:13] Number of windows considered: 1...
[2021-11-02 11:26:13] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:26:13] Done.
Validation 2, 20 remaining
[2021-11-02 11:26:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:14] Number of windows considered: 1...
[2021-11-02 11:26:14] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:26:14] Done.
Validation 3, 19 remaining
[2021-11-02 11:26:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:16] Number of windows considered: 1...
[2021-11-02 11:26:16] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:26:16] Done.
Validation 4, 18 remaining
[2021-11-02 11:26:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:17] Number of windows considered: 1...
[2021-11-02 11:26:17] Bias-correcting 1 members separately...
[2021-11-02 11:26:18] Done.
Validation 5, 17 remaining
[2021-11-02 11:26:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:19] Number of windows considered: 1...
[2021-11-02 11:26:19] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:26:19] Done.
Validation 6, 16 remaining
[2021-11-02 11:26:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:21] Number of windows considered: 1...
[2021-11-02 11:26:21] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:26:21] Done.
Validation 7, 15 remaining
[2021-11-02 11:26:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:23] Number of windows considered: 1...
[2021-11-02 11:26:23] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:26:23] Done.
Validation 8, 14 remaining
[2021-11-02 11:26:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:25] Number of windows considered: 1...
[2021-11-02 11:26:25] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:26:26] Done.
Validation 9, 13 remaining
[2021-11-02 11:26:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:27] Number of windows considered: 1...
[2021-11-02 11:26:27] Bias-correcting 1 members separately...
[2021-11-02 11:26:27] Done.
Validation 10, 12 remaining
[2021-11-02 11:26:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:28] Number of windows considered: 1...
[2021-11-02 11:26:28] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:26:29] Done.
Validation 11, 11 remaining
[2021-11-02 11:26:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:30] Number of windows considered: 1...
[2021-11-02 11:26:30] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:26:30] Done.
Validation 12, 10 remaining
[2021-11-02 11:26:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:31] Number of windows considered: 1...
[2021-11-02 11:26:31] Bias-correcting 1 members separately...
NaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:26:31] Done.
Validation 13, 9 remaining
[2021-11-02 11:26:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:33] Number of windows considered: 1...
[2021-11-02 11:26:33] Bias-correcting 1 members separately...
[2021-11-02 11:26:33] Done.
Validation 14, 8 remaining
[2021-11-02 11:26:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:34] Number of windows considered: 1...
[2021-11-02 11:26:34] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:26:34] Done.
Validation 15, 7 remaining
[2021-11-02 11:26:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:35] Number of windows considered: 1...
[2021-11-02 11:26:35] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:26:35] Done.
Validation 16, 6 remaining
[2021-11-02 11:26:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:37] Number of windows considered: 1...
[2021-11-02 11:26:37] Bias-correcting 1 members separately...
[2021-11-02 11:26:37] Done.
Validation 17, 5 remaining
[2021-11-02 11:26:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:39] Number of windows considered: 1...
[2021-11-02 11:26:39] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:26:39] Done.
Validation 18, 4 remaining
[2021-11-02 11:26:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:41] Number of windows considered: 1...
[2021-11-02 11:26:41] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:26:42] Done.
Validation 19, 3 remaining
[2021-11-02 11:26:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:43] Number of windows considered: 1...
[2021-11-02 11:26:43] Bias-correcting 1 members separately...
[2021-11-02 11:26:43] Done.
Validation 20, 2 remaining
[2021-11-02 11:26:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:44] Number of windows considered: 1...
[2021-11-02 11:26:44] Bias-correcting 1 members separately...
[2021-11-02 11:26:45] Done.
Validation 21, 1 remaining
[2021-11-02 11:26:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:46] Number of windows considered: 1...
[2021-11-02 11:26:46] Bias-correcting 1 members separately...
[2021-11-02 11:26:46] Done.
Validation 22, 0 remaining
[2021-11-02 11:26:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:48] Number of windows considered: 1...
[2021-11-02 11:26:48] Bias-correcting 1 members separately...
[2021-11-02 11:26:48] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-11-02 11:26:48] Performing annual aggregation...
[2021-11-02 11:26:48] Done.
[2021-11-02 11:26:48] - Computing climatology...
[2021-11-02 11:26:48] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm.cl3 <- index.cal.station.cl3
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:26:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:51] Number of windows considered: 1...
[2021-11-02 11:26:51] Bias-correcting 1 members separately...
[2021-11-02 11:26:51] Done.
Validation 2, 20 remaining
[2021-11-02 11:26:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:53] Number of windows considered: 1...
[2021-11-02 11:26:53] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:26:53] Done.
Validation 3, 19 remaining
[2021-11-02 11:26:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:54] Number of windows considered: 1...
[2021-11-02 11:26:54] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:26:54] Done.
Validation 4, 18 remaining
[2021-11-02 11:26:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:56] Number of windows considered: 1...
[2021-11-02 11:26:56] Bias-correcting 1 members separately...
[2021-11-02 11:26:56] Done.
Validation 5, 17 remaining
[2021-11-02 11:26:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:57] Number of windows considered: 1...
[2021-11-02 11:26:57] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:26:58] Done.
Validation 6, 16 remaining
[2021-11-02 11:26:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:26:59] Number of windows considered: 1...
[2021-11-02 11:26:59] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:26:59] Done.
Validation 7, 15 remaining
[2021-11-02 11:27:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:00] Number of windows considered: 1...
[2021-11-02 11:27:00] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:27:00] Done.
Validation 8, 14 remaining
[2021-11-02 11:27:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:01] Number of windows considered: 1...
[2021-11-02 11:27:01] Bias-correcting 1 members separately...
[2021-11-02 11:27:01] Done.
Validation 9, 13 remaining
[2021-11-02 11:27:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:02] Number of windows considered: 1...
[2021-11-02 11:27:02] Bias-correcting 1 members separately...
[2021-11-02 11:27:02] Done.
Validation 10, 12 remaining
[2021-11-02 11:27:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:03] Number of windows considered: 1...
[2021-11-02 11:27:03] Bias-correcting 1 members separately...
[2021-11-02 11:27:03] Done.
Validation 11, 11 remaining
[2021-11-02 11:27:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:04] Number of windows considered: 1...
[2021-11-02 11:27:04] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:27:04] Done.
Validation 12, 10 remaining
[2021-11-02 11:27:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:05] Number of windows considered: 1...
[2021-11-02 11:27:05] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:27:05] Done.
Validation 13, 9 remaining
[2021-11-02 11:27:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:06] Number of windows considered: 1...
[2021-11-02 11:27:06] Bias-correcting 1 members separately...
[2021-11-02 11:27:06] Done.
Validation 14, 8 remaining
[2021-11-02 11:27:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:07] Number of windows considered: 1...
[2021-11-02 11:27:07] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:27:07] Done.
Validation 15, 7 remaining
[2021-11-02 11:27:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:08] Number of windows considered: 1...
[2021-11-02 11:27:08] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:27:08] Done.
Validation 16, 6 remaining
[2021-11-02 11:27:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:09] Number of windows considered: 1...
[2021-11-02 11:27:09] Bias-correcting 1 members separately...
[2021-11-02 11:27:10] Done.
Validation 17, 5 remaining
[2021-11-02 11:27:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:10] Number of windows considered: 1...
[2021-11-02 11:27:10] Bias-correcting 1 members separately...
[2021-11-02 11:27:10] Done.
Validation 18, 4 remaining
[2021-11-02 11:27:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:11] Number of windows considered: 1...
[2021-11-02 11:27:11] Bias-correcting 1 members separately...
[2021-11-02 11:27:12] Done.
Validation 19, 3 remaining
[2021-11-02 11:27:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:13] Number of windows considered: 1...
[2021-11-02 11:27:13] Bias-correcting 1 members separately...
[2021-11-02 11:27:13] Done.
Validation 20, 2 remaining
[2021-11-02 11:27:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:14] Number of windows considered: 1...
[2021-11-02 11:27:14] Bias-correcting 1 members separately...
[2021-11-02 11:27:14] Done.
Validation 21, 1 remaining
[2021-11-02 11:27:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:15] Number of windows considered: 1...
[2021-11-02 11:27:15] Bias-correcting 1 members separately...
[2021-11-02 11:27:15] Done.
Validation 22, 0 remaining
[2021-11-02 11:27:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:16] Number of windows considered: 1...
[2021-11-02 11:27:16] Bias-correcting 1 members separately...
[2021-11-02 11:27:16] Done.
cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))
cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")
index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)
[2021-11-02 11:27:16] Performing annual aggregation...
[2021-11-02 11:27:16] Done.
[2021-11-02 11:27:16] - Computing climatology...
[2021-11-02 11:27:16] - Done.
index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)
index.cal.station.gpqm2.cl3 <- index.cal.station.cl3
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
PQM-WT3 GPQM2-WT3 EQM-WT3 GPQM-WT3
0.9194684 0.7269962 0.7034516 0.1232687
scores.st7.wt3 <- scores
WT4
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))
station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
[2021-11-02 11:27:17] Performing annual aggregation...
[2021-11-02 11:27:17] Done.
[2021-11-02 11:27:17] - Computing climatology...
[2021-11-02 11:27:17] - Done.
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)
index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
[2021-11-02 11:27:17] Performing annual aggregation...
[2021-11-02 11:27:17] Done.
[2021-11-02 11:27:17] - Computing climatology...
[2021-11-02 11:27:17] - Done.
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")
station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:27:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:19] Number of windows considered: 1...
[2021-11-02 11:27:19] Bias-correcting 1 members separately...
[2021-11-02 11:27:19] Done.
Validation 2, 20 remaining
[2021-11-02 11:27:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:20] Number of windows considered: 1...
[2021-11-02 11:27:20] Bias-correcting 1 members separately...
[2021-11-02 11:27:20] Done.
Validation 3, 19 remaining
[2021-11-02 11:27:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:21] Number of windows considered: 1...
[2021-11-02 11:27:21] Bias-correcting 1 members separately...
[2021-11-02 11:27:21] Done.
Validation 4, 18 remaining
[2021-11-02 11:27:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:23] Number of windows considered: 1...
[2021-11-02 11:27:23] Bias-correcting 1 members separately...
[2021-11-02 11:27:23] Done.
Validation 5, 17 remaining
[2021-11-02 11:27:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:24] Number of windows considered: 1...
[2021-11-02 11:27:24] Bias-correcting 1 members separately...
[2021-11-02 11:27:24] Done.
Validation 6, 16 remaining
[2021-11-02 11:27:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:26] Number of windows considered: 1...
[2021-11-02 11:27:26] Bias-correcting 1 members separately...
[2021-11-02 11:27:26] Done.
Validation 7, 15 remaining
[2021-11-02 11:27:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:28] Number of windows considered: 1...
[2021-11-02 11:27:28] Bias-correcting 1 members separately...
[2021-11-02 11:27:28] Done.
Validation 8, 14 remaining
[2021-11-02 11:27:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:30] Number of windows considered: 1...
[2021-11-02 11:27:30] Bias-correcting 1 members separately...
[2021-11-02 11:27:30] Done.
Validation 9, 13 remaining
[2021-11-02 11:27:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:31] Number of windows considered: 1...
[2021-11-02 11:27:31] Bias-correcting 1 members separately...
[2021-11-02 11:27:31] Done.
Validation 10, 12 remaining
[2021-11-02 11:27:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:32] Number of windows considered: 1...
[2021-11-02 11:27:32] Bias-correcting 1 members separately...
[2021-11-02 11:27:32] Done.
Validation 11, 11 remaining
[2021-11-02 11:27:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:34] Number of windows considered: 1...
[2021-11-02 11:27:34] Bias-correcting 1 members separately...
[2021-11-02 11:27:34] Done.
Validation 12, 10 remaining
[2021-11-02 11:27:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:36] Number of windows considered: 1...
[2021-11-02 11:27:36] Bias-correcting 1 members separately...
[2021-11-02 11:27:36] Done.
Validation 13, 9 remaining
[2021-11-02 11:27:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:38] Number of windows considered: 1...
[2021-11-02 11:27:38] Bias-correcting 1 members separately...
[2021-11-02 11:27:38] Done.
Validation 14, 8 remaining
[2021-11-02 11:27:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:39] Number of windows considered: 1...
[2021-11-02 11:27:39] Bias-correcting 1 members separately...
[2021-11-02 11:27:39] Done.
Validation 15, 7 remaining
[2021-11-02 11:27:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:40] Number of windows considered: 1...
[2021-11-02 11:27:40] Bias-correcting 1 members separately...
[2021-11-02 11:27:40] Done.
Validation 16, 6 remaining
[2021-11-02 11:27:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:42] Number of windows considered: 1...
[2021-11-02 11:27:42] Bias-correcting 1 members separately...
[2021-11-02 11:27:42] Done.
Validation 17, 5 remaining
[2021-11-02 11:27:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:43] Number of windows considered: 1...
[2021-11-02 11:27:43] Bias-correcting 1 members separately...
[2021-11-02 11:27:43] Done.
Validation 18, 4 remaining
[2021-11-02 11:27:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:44] Number of windows considered: 1...
[2021-11-02 11:27:44] Bias-correcting 1 members separately...
[2021-11-02 11:27:44] Done.
Validation 19, 3 remaining
[2021-11-02 11:27:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:46] Number of windows considered: 1...
[2021-11-02 11:27:46] Bias-correcting 1 members separately...
[2021-11-02 11:27:46] Done.
Validation 20, 2 remaining
[2021-11-02 11:27:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:47] Number of windows considered: 1...
[2021-11-02 11:27:47] Bias-correcting 1 members separately...
[2021-11-02 11:27:47] Done.
Validation 21, 1 remaining
[2021-11-02 11:27:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:48] Number of windows considered: 1...
[2021-11-02 11:27:48] Bias-correcting 1 members separately...
[2021-11-02 11:27:48] Done.
Validation 22, 0 remaining
[2021-11-02 11:27:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:49] Number of windows considered: 1...
[2021-11-02 11:27:49] Bias-correcting 1 members separately...
[2021-11-02 11:27:49] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-11-02 11:27:50] Performing annual aggregation...
[2021-11-02 11:27:50] Done.
[2021-11-02 11:27:50] - Computing climatology...
[2021-11-02 11:27:50] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.pqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:27:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:51] Number of windows considered: 1...
[2021-11-02 11:27:51] Bias-correcting 1 members separately...
[2021-11-02 11:27:52] Done.
Validation 2, 20 remaining
[2021-11-02 11:27:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:53] Number of windows considered: 1...
[2021-11-02 11:27:53] Bias-correcting 1 members separately...
[2021-11-02 11:27:53] Done.
Validation 3, 19 remaining
[2021-11-02 11:27:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:54] Number of windows considered: 1...
[2021-11-02 11:27:54] Bias-correcting 1 members separately...
[2021-11-02 11:27:54] Done.
Validation 4, 18 remaining
[2021-11-02 11:27:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:56] Number of windows considered: 1...
[2021-11-02 11:27:56] Bias-correcting 1 members separately...
[2021-11-02 11:27:56] Done.
Validation 5, 17 remaining
[2021-11-02 11:27:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:57] Number of windows considered: 1...
[2021-11-02 11:27:57] Bias-correcting 1 members separately...
[2021-11-02 11:27:57] Done.
Validation 6, 16 remaining
[2021-11-02 11:27:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:27:58] Number of windows considered: 1...
[2021-11-02 11:27:58] Bias-correcting 1 members separately...
[2021-11-02 11:27:58] Done.
Validation 7, 15 remaining
[2021-11-02 11:28:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:00] Number of windows considered: 1...
[2021-11-02 11:28:00] Bias-correcting 1 members separately...
[2021-11-02 11:28:00] Done.
Validation 8, 14 remaining
[2021-11-02 11:28:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:01] Number of windows considered: 1...
[2021-11-02 11:28:01] Bias-correcting 1 members separately...
[2021-11-02 11:28:01] Done.
Validation 9, 13 remaining
[2021-11-02 11:28:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:02] Number of windows considered: 1...
[2021-11-02 11:28:02] Bias-correcting 1 members separately...
[2021-11-02 11:28:03] Done.
Validation 10, 12 remaining
[2021-11-02 11:28:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:04] Number of windows considered: 1...
[2021-11-02 11:28:04] Bias-correcting 1 members separately...
[2021-11-02 11:28:04] Done.
Validation 11, 11 remaining
[2021-11-02 11:28:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:05] Number of windows considered: 1...
[2021-11-02 11:28:05] Bias-correcting 1 members separately...
[2021-11-02 11:28:05] Done.
Validation 12, 10 remaining
[2021-11-02 11:28:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:06] Number of windows considered: 1...
[2021-11-02 11:28:06] Bias-correcting 1 members separately...
[2021-11-02 11:28:07] Done.
Validation 13, 9 remaining
[2021-11-02 11:28:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:08] Number of windows considered: 1...
[2021-11-02 11:28:08] Bias-correcting 1 members separately...
[2021-11-02 11:28:08] Done.
Validation 14, 8 remaining
[2021-11-02 11:28:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:09] Number of windows considered: 1...
[2021-11-02 11:28:09] Bias-correcting 1 members separately...
[2021-11-02 11:28:09] Done.
Validation 15, 7 remaining
[2021-11-02 11:28:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:10] Number of windows considered: 1...
[2021-11-02 11:28:10] Bias-correcting 1 members separately...
[2021-11-02 11:28:10] Done.
Validation 16, 6 remaining
[2021-11-02 11:28:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:12] Number of windows considered: 1...
[2021-11-02 11:28:12] Bias-correcting 1 members separately...
[2021-11-02 11:28:12] Done.
Validation 17, 5 remaining
[2021-11-02 11:28:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:13] Number of windows considered: 1...
[2021-11-02 11:28:13] Bias-correcting 1 members separately...
[2021-11-02 11:28:13] Done.
Validation 18, 4 remaining
[2021-11-02 11:28:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:14] Number of windows considered: 1...
[2021-11-02 11:28:14] Bias-correcting 1 members separately...
[2021-11-02 11:28:14] Done.
Validation 19, 3 remaining
[2021-11-02 11:28:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:16] Number of windows considered: 1...
[2021-11-02 11:28:16] Bias-correcting 1 members separately...
[2021-11-02 11:28:16] Done.
Validation 20, 2 remaining
[2021-11-02 11:28:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:17] Number of windows considered: 1...
[2021-11-02 11:28:17] Bias-correcting 1 members separately...
[2021-11-02 11:28:17] Done.
Validation 21, 1 remaining
[2021-11-02 11:28:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:18] Number of windows considered: 1...
[2021-11-02 11:28:18] Bias-correcting 1 members separately...
[2021-11-02 11:28:18] Done.
Validation 22, 0 remaining
[2021-11-02 11:28:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:20] Number of windows considered: 1...
[2021-11-02 11:28:20] Bias-correcting 1 members separately...
[2021-11-02 11:28:20] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-11-02 11:28:21] Performing annual aggregation...
[2021-11-02 11:28:21] Done.
[2021-11-02 11:28:21] - Computing climatology...
[2021-11-02 11:28:21] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.eqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:28:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:23] Number of windows considered: 1...
[2021-11-02 11:28:23] Bias-correcting 1 members separately...
[2021-11-02 11:28:23] Done.
Validation 2, 20 remaining
[2021-11-02 11:28:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:24] Number of windows considered: 1...
[2021-11-02 11:28:24] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:28:24] Done.
Validation 3, 19 remaining
[2021-11-02 11:28:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:25] Number of windows considered: 1...
[2021-11-02 11:28:25] Bias-correcting 1 members separately...
[2021-11-02 11:28:26] Done.
Validation 4, 18 remaining
[2021-11-02 11:28:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:27] Number of windows considered: 1...
[2021-11-02 11:28:27] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:28:27] Done.
Validation 5, 17 remaining
[2021-11-02 11:28:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:28] Number of windows considered: 1...
[2021-11-02 11:28:28] Bias-correcting 1 members separately...
[2021-11-02 11:28:28] Done.
Validation 6, 16 remaining
[2021-11-02 11:28:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:29] Number of windows considered: 1...
[2021-11-02 11:28:29] Bias-correcting 1 members separately...
[2021-11-02 11:28:29] Done.
Validation 7, 15 remaining
[2021-11-02 11:28:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:30] Number of windows considered: 1...
[2021-11-02 11:28:30] Bias-correcting 1 members separately...
[2021-11-02 11:28:30] Done.
Validation 8, 14 remaining
[2021-11-02 11:28:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:32] Number of windows considered: 1...
[2021-11-02 11:28:32] Bias-correcting 1 members separately...
[2021-11-02 11:28:32] Done.
Validation 9, 13 remaining
[2021-11-02 11:28:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:33] Number of windows considered: 1...
[2021-11-02 11:28:33] Bias-correcting 1 members separately...
[2021-11-02 11:28:33] Done.
Validation 10, 12 remaining
[2021-11-02 11:28:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:34] Number of windows considered: 1...
[2021-11-02 11:28:34] Bias-correcting 1 members separately...
[2021-11-02 11:28:34] Done.
Validation 11, 11 remaining
[2021-11-02 11:28:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:35] Number of windows considered: 1...
[2021-11-02 11:28:35] Bias-correcting 1 members separately...
[2021-11-02 11:28:35] Done.
Validation 12, 10 remaining
[2021-11-02 11:28:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:36] Number of windows considered: 1...
[2021-11-02 11:28:36] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:28:37] Done.
Validation 13, 9 remaining
[2021-11-02 11:28:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:38] Number of windows considered: 1...
[2021-11-02 11:28:38] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:28:38] Done.
Validation 14, 8 remaining
[2021-11-02 11:28:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:39] Number of windows considered: 1...
[2021-11-02 11:28:39] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:28:39] Done.
Validation 15, 7 remaining
[2021-11-02 11:28:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:40] Number of windows considered: 1...
[2021-11-02 11:28:40] Bias-correcting 1 members separately...
[2021-11-02 11:28:40] Done.
Validation 16, 6 remaining
[2021-11-02 11:28:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:41] Number of windows considered: 1...
[2021-11-02 11:28:41] Bias-correcting 1 members separately...
[2021-11-02 11:28:41] Done.
Validation 17, 5 remaining
[2021-11-02 11:28:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:42] Number of windows considered: 1...
[2021-11-02 11:28:42] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:28:42] Done.
Validation 18, 4 remaining
[2021-11-02 11:28:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:43] Number of windows considered: 1...
[2021-11-02 11:28:43] Bias-correcting 1 members separately...
[2021-11-02 11:28:44] Done.
Validation 19, 3 remaining
[2021-11-02 11:28:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:45] Number of windows considered: 1...
[2021-11-02 11:28:45] Bias-correcting 1 members separately...
[2021-11-02 11:28:45] Done.
Validation 20, 2 remaining
[2021-11-02 11:28:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:46] Number of windows considered: 1...
[2021-11-02 11:28:46] Bias-correcting 1 members separately...
no non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:28:46] Done.
Validation 21, 1 remaining
[2021-11-02 11:28:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:47] Number of windows considered: 1...
[2021-11-02 11:28:47] Bias-correcting 1 members separately...
[2021-11-02 11:28:47] Done.
Validation 22, 0 remaining
[2021-11-02 11:28:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:48] Number of windows considered: 1...
[2021-11-02 11:28:48] Bias-correcting 1 members separately...
[2021-11-02 11:28:48] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-11-02 11:28:49] Performing annual aggregation...
[2021-11-02 11:28:49] Done.
[2021-11-02 11:28:49] - Computing climatology...
[2021-11-02 11:28:49] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm.cl4 <- index.cal.station.cl4
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:28:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:50] Number of windows considered: 1...
[2021-11-02 11:28:50] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:28:50] Done.
Validation 2, 20 remaining
[2021-11-02 11:28:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:51] Number of windows considered: 1...
[2021-11-02 11:28:51] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:28:52] Done.
Validation 3, 19 remaining
[2021-11-02 11:28:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:53] Number of windows considered: 1...
[2021-11-02 11:28:53] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:28:53] Done.
Validation 4, 18 remaining
[2021-11-02 11:28:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:54] Number of windows considered: 1...
[2021-11-02 11:28:54] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:28:54] Done.
Validation 5, 17 remaining
[2021-11-02 11:28:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:55] Number of windows considered: 1...
[2021-11-02 11:28:55] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:28:55] Done.
Validation 6, 16 remaining
[2021-11-02 11:28:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:56] Number of windows considered: 1...
[2021-11-02 11:28:56] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:28:56] Done.
Validation 7, 15 remaining
[2021-11-02 11:28:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:57] Number of windows considered: 1...
[2021-11-02 11:28:57] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:28:57] Done.
Validation 8, 14 remaining
[2021-11-02 11:28:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:58] Number of windows considered: 1...
[2021-11-02 11:28:58] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:28:58] Done.
Validation 9, 13 remaining
[2021-11-02 11:28:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:28:59] Number of windows considered: 1...
[2021-11-02 11:28:59] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:00] Done.
Validation 10, 12 remaining
[2021-11-02 11:29:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:00] Number of windows considered: 1...
[2021-11-02 11:29:00] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:01] Done.
Validation 11, 11 remaining
[2021-11-02 11:29:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:01] Number of windows considered: 1...
[2021-11-02 11:29:01] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:02] Done.
Validation 12, 10 remaining
[2021-11-02 11:29:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:02] Number of windows considered: 1...
[2021-11-02 11:29:02] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:02] Done.
Validation 13, 9 remaining
[2021-11-02 11:29:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:04] Number of windows considered: 1...
[2021-11-02 11:29:04] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:04] Done.
Validation 14, 8 remaining
[2021-11-02 11:29:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:05] Number of windows considered: 1...
[2021-11-02 11:29:05] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:05] Done.
Validation 15, 7 remaining
[2021-11-02 11:29:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:06] Number of windows considered: 1...
[2021-11-02 11:29:06] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:06] Done.
Validation 16, 6 remaining
[2021-11-02 11:29:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:07] Number of windows considered: 1...
[2021-11-02 11:29:07] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:07] Done.
Validation 17, 5 remaining
[2021-11-02 11:29:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:08] Number of windows considered: 1...
[2021-11-02 11:29:08] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:08] Done.
Validation 18, 4 remaining
[2021-11-02 11:29:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:09] Number of windows considered: 1...
[2021-11-02 11:29:09] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:09] Done.
Validation 19, 3 remaining
[2021-11-02 11:29:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:10] Number of windows considered: 1...
[2021-11-02 11:29:10] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:10] Done.
Validation 20, 2 remaining
[2021-11-02 11:29:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:11] Number of windows considered: 1...
[2021-11-02 11:29:11] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:11] Done.
Validation 21, 1 remaining
[2021-11-02 11:29:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:12] Number of windows considered: 1...
[2021-11-02 11:29:12] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:12] Done.
Validation 22, 0 remaining
[2021-11-02 11:29:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:13] Number of windows considered: 1...
[2021-11-02 11:29:13] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:29:13] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))
cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")
index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)
[2021-11-02 11:29:14] Performing annual aggregation...
[2021-11-02 11:29:14] Done.
[2021-11-02 11:29:14] - Computing climatology...
[2021-11-02 11:29:14] - Done.
index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)
index.cal.station.gpqm2.cl4 <- index.cal.station.cl4
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)
scores
EQM-WT4 PQM-WT4 GPQM2-WT4 GPQM-WT4
0.6800771 0.5449438 0.4167663 0.3703024
scores.st7.wt4 <- scores
WT5
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))
station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
[2021-11-02 11:29:14] Performing annual aggregation...
[2021-11-02 11:29:14] Done.
[2021-11-02 11:29:14] - Computing climatology...
[2021-11-02 11:29:14] - Done.
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)
index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
[2021-11-02 11:29:15] Performing annual aggregation...
[2021-11-02 11:29:15] Done.
[2021-11-02 11:29:15] - Computing climatology...
[2021-11-02 11:29:15] - Done.
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")
station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:29:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:16] Number of windows considered: 1...
[2021-11-02 11:29:16] Bias-correcting 1 members separately...
[2021-11-02 11:29:16] Done.
Validation 2, 20 remaining
[2021-11-02 11:29:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:17] Number of windows considered: 1...
[2021-11-02 11:29:17] Bias-correcting 1 members separately...
[2021-11-02 11:29:17] Done.
Validation 3, 19 remaining
[2021-11-02 11:29:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:18] Number of windows considered: 1...
[2021-11-02 11:29:18] Bias-correcting 1 members separately...
[2021-11-02 11:29:18] Done.
Validation 4, 18 remaining
[2021-11-02 11:29:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:19] Number of windows considered: 1...
[2021-11-02 11:29:19] Bias-correcting 1 members separately...
[2021-11-02 11:29:19] Done.
Validation 5, 17 remaining
[2021-11-02 11:29:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:21] Number of windows considered: 1...
[2021-11-02 11:29:21] Bias-correcting 1 members separately...
[2021-11-02 11:29:21] Done.
Validation 6, 16 remaining
[2021-11-02 11:29:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:22] Number of windows considered: 1...
[2021-11-02 11:29:22] Bias-correcting 1 members separately...
[2021-11-02 11:29:22] Done.
Validation 7, 15 remaining
[2021-11-02 11:29:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:24] Number of windows considered: 1...
[2021-11-02 11:29:24] Bias-correcting 1 members separately...
[2021-11-02 11:29:24] Done.
Validation 8, 14 remaining
[2021-11-02 11:29:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:25] Number of windows considered: 1...
[2021-11-02 11:29:25] Bias-correcting 1 members separately...
[2021-11-02 11:29:25] Done.
Validation 9, 13 remaining
[2021-11-02 11:29:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:26] Number of windows considered: 1...
[2021-11-02 11:29:26] Bias-correcting 1 members separately...
[2021-11-02 11:29:26] Done.
Validation 10, 12 remaining
[2021-11-02 11:29:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:27] Number of windows considered: 1...
[2021-11-02 11:29:27] Bias-correcting 1 members separately...
[2021-11-02 11:29:27] Done.
Validation 11, 11 remaining
[2021-11-02 11:29:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:28] Number of windows considered: 1...
[2021-11-02 11:29:28] Bias-correcting 1 members separately...
[2021-11-02 11:29:28] Done.
Validation 12, 10 remaining
[2021-11-02 11:29:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:29] Number of windows considered: 1...
[2021-11-02 11:29:29] Bias-correcting 1 members separately...
[2021-11-02 11:29:29] Done.
Validation 13, 9 remaining
[2021-11-02 11:29:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:30] Number of windows considered: 1...
[2021-11-02 11:29:30] Bias-correcting 1 members separately...
[2021-11-02 11:29:30] Done.
Validation 14, 8 remaining
[2021-11-02 11:29:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:31] Number of windows considered: 1...
[2021-11-02 11:29:31] Bias-correcting 1 members separately...
[2021-11-02 11:29:31] Done.
Validation 15, 7 remaining
[2021-11-02 11:29:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:32] Number of windows considered: 1...
[2021-11-02 11:29:32] Bias-correcting 1 members separately...
[2021-11-02 11:29:32] Done.
Validation 16, 6 remaining
[2021-11-02 11:29:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:33] Number of windows considered: 1...
[2021-11-02 11:29:33] Bias-correcting 1 members separately...
[2021-11-02 11:29:33] Done.
Validation 17, 5 remaining
[2021-11-02 11:29:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:35] Number of windows considered: 1...
[2021-11-02 11:29:35] Bias-correcting 1 members separately...
[2021-11-02 11:29:35] Done.
Validation 18, 4 remaining
[2021-11-02 11:29:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:36] Number of windows considered: 1...
[2021-11-02 11:29:36] Bias-correcting 1 members separately...
[2021-11-02 11:29:36] Done.
Validation 19, 3 remaining
[2021-11-02 11:29:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:37] Number of windows considered: 1...
[2021-11-02 11:29:37] Bias-correcting 1 members separately...
[2021-11-02 11:29:37] Done.
Validation 20, 2 remaining
[2021-11-02 11:29:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:38] Number of windows considered: 1...
[2021-11-02 11:29:38] Bias-correcting 1 members separately...
[2021-11-02 11:29:38] Done.
Validation 21, 1 remaining
[2021-11-02 11:29:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:39] Number of windows considered: 1...
[2021-11-02 11:29:39] Bias-correcting 1 members separately...
[2021-11-02 11:29:39] Done.
Validation 22, 0 remaining
[2021-11-02 11:29:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:40] Number of windows considered: 1...
[2021-11-02 11:29:40] Bias-correcting 1 members separately...
[2021-11-02 11:29:40] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-11-02 11:29:41] Performing annual aggregation...
[2021-11-02 11:29:41] Done.
[2021-11-02 11:29:41] - Computing climatology...
[2021-11-02 11:29:41] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.pqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:29:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:42] Number of windows considered: 1...
[2021-11-02 11:29:42] Bias-correcting 1 members separately...
[2021-11-02 11:29:43] Done.
Validation 2, 20 remaining
[2021-11-02 11:29:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:44] Number of windows considered: 1...
[2021-11-02 11:29:44] Bias-correcting 1 members separately...
[2021-11-02 11:29:44] Done.
Validation 3, 19 remaining
[2021-11-02 11:29:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:45] Number of windows considered: 1...
[2021-11-02 11:29:45] Bias-correcting 1 members separately...
[2021-11-02 11:29:45] Done.
Validation 4, 18 remaining
[2021-11-02 11:29:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:46] Number of windows considered: 1...
[2021-11-02 11:29:46] Bias-correcting 1 members separately...
[2021-11-02 11:29:47] Done.
Validation 5, 17 remaining
[2021-11-02 11:29:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:48] Number of windows considered: 1...
[2021-11-02 11:29:48] Bias-correcting 1 members separately...
[2021-11-02 11:29:48] Done.
Validation 6, 16 remaining
[2021-11-02 11:29:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:50] Number of windows considered: 1...
[2021-11-02 11:29:50] Bias-correcting 1 members separately...
[2021-11-02 11:29:50] Done.
Validation 7, 15 remaining
[2021-11-02 11:29:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:52] Number of windows considered: 1...
[2021-11-02 11:29:52] Bias-correcting 1 members separately...
[2021-11-02 11:29:52] Done.
Validation 8, 14 remaining
[2021-11-02 11:29:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:53] Number of windows considered: 1...
[2021-11-02 11:29:53] Bias-correcting 1 members separately...
[2021-11-02 11:29:53] Done.
Validation 9, 13 remaining
[2021-11-02 11:29:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:54] Number of windows considered: 1...
[2021-11-02 11:29:54] Bias-correcting 1 members separately...
[2021-11-02 11:29:54] Done.
Validation 10, 12 remaining
[2021-11-02 11:29:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:55] Number of windows considered: 1...
[2021-11-02 11:29:55] Bias-correcting 1 members separately...
[2021-11-02 11:29:56] Done.
Validation 11, 11 remaining
[2021-11-02 11:29:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:57] Number of windows considered: 1...
[2021-11-02 11:29:57] Bias-correcting 1 members separately...
[2021-11-02 11:29:57] Done.
Validation 12, 10 remaining
[2021-11-02 11:29:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:58] Number of windows considered: 1...
[2021-11-02 11:29:58] Bias-correcting 1 members separately...
[2021-11-02 11:29:58] Done.
Validation 13, 9 remaining
[2021-11-02 11:29:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:29:59] Number of windows considered: 1...
[2021-11-02 11:29:59] Bias-correcting 1 members separately...
[2021-11-02 11:29:59] Done.
Validation 14, 8 remaining
[2021-11-02 11:30:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:00] Number of windows considered: 1...
[2021-11-02 11:30:00] Bias-correcting 1 members separately...
[2021-11-02 11:30:01] Done.
Validation 15, 7 remaining
[2021-11-02 11:30:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:02] Number of windows considered: 1...
[2021-11-02 11:30:02] Bias-correcting 1 members separately...
[2021-11-02 11:30:02] Done.
Validation 16, 6 remaining
[2021-11-02 11:30:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:03] Number of windows considered: 1...
[2021-11-02 11:30:03] Bias-correcting 1 members separately...
[2021-11-02 11:30:03] Done.
Validation 17, 5 remaining
[2021-11-02 11:30:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:04] Number of windows considered: 1...
[2021-11-02 11:30:04] Bias-correcting 1 members separately...
[2021-11-02 11:30:05] Done.
Validation 18, 4 remaining
[2021-11-02 11:30:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:06] Number of windows considered: 1...
[2021-11-02 11:30:06] Bias-correcting 1 members separately...
[2021-11-02 11:30:06] Done.
Validation 19, 3 remaining
[2021-11-02 11:30:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:07] Number of windows considered: 1...
[2021-11-02 11:30:07] Bias-correcting 1 members separately...
[2021-11-02 11:30:07] Done.
Validation 20, 2 remaining
[2021-11-02 11:30:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:08] Number of windows considered: 1...
[2021-11-02 11:30:08] Bias-correcting 1 members separately...
[2021-11-02 11:30:08] Done.
Validation 21, 1 remaining
[2021-11-02 11:30:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:09] Number of windows considered: 1...
[2021-11-02 11:30:09] Bias-correcting 1 members separately...
[2021-11-02 11:30:09] Done.
Validation 22, 0 remaining
[2021-11-02 11:30:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:11] Number of windows considered: 1...
[2021-11-02 11:30:11] Bias-correcting 1 members separately...
[2021-11-02 11:30:11] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-11-02 11:30:11] Performing annual aggregation...
[2021-11-02 11:30:11] Done.
[2021-11-02 11:30:11] - Computing climatology...
[2021-11-02 11:30:11] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.eqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:30:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:13] Number of windows considered: 1...
[2021-11-02 11:30:13] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:13] Done.
Validation 2, 20 remaining
[2021-11-02 11:30:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:14] Number of windows considered: 1...
[2021-11-02 11:30:14] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:14] Done.
Validation 3, 19 remaining
[2021-11-02 11:30:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:16] Number of windows considered: 1...
[2021-11-02 11:30:16] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:16] Done.
Validation 4, 18 remaining
[2021-11-02 11:30:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:17] Number of windows considered: 1...
[2021-11-02 11:30:17] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:18] Done.
Validation 5, 17 remaining
[2021-11-02 11:30:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:19] Number of windows considered: 1...
[2021-11-02 11:30:19] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:19] Done.
Validation 6, 16 remaining
[2021-11-02 11:30:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:20] Number of windows considered: 1...
[2021-11-02 11:30:20] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:20] Done.
Validation 7, 15 remaining
[2021-11-02 11:30:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:21] Number of windows considered: 1...
[2021-11-02 11:30:21] Bias-correcting 1 members separately...
NaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:30:22] Done.
Validation 8, 14 remaining
[2021-11-02 11:30:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:23] Number of windows considered: 1...
[2021-11-02 11:30:23] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:23] Done.
Validation 9, 13 remaining
[2021-11-02 11:30:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:24] Number of windows considered: 1...
[2021-11-02 11:30:24] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:24] Done.
Validation 10, 12 remaining
[2021-11-02 11:30:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:25] Number of windows considered: 1...
[2021-11-02 11:30:25] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:26] Done.
Validation 11, 11 remaining
[2021-11-02 11:30:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:27] Number of windows considered: 1...
[2021-11-02 11:30:27] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:27] Done.
Validation 12, 10 remaining
[2021-11-02 11:30:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:28] Number of windows considered: 1...
[2021-11-02 11:30:28] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:28] Done.
Validation 13, 9 remaining
[2021-11-02 11:30:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:29] Number of windows considered: 1...
[2021-11-02 11:30:29] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:29] Done.
Validation 14, 8 remaining
[2021-11-02 11:30:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:31] Number of windows considered: 1...
[2021-11-02 11:30:31] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:31] Done.
Validation 15, 7 remaining
[2021-11-02 11:30:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:32] Number of windows considered: 1...
[2021-11-02 11:30:32] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:32] Done.
Validation 16, 6 remaining
[2021-11-02 11:30:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:33] Number of windows considered: 1...
[2021-11-02 11:30:33] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:34] Done.
Validation 17, 5 remaining
[2021-11-02 11:30:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:35] Number of windows considered: 1...
[2021-11-02 11:30:35] Bias-correcting 1 members separately...
NaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:30:35] Done.
Validation 18, 4 remaining
[2021-11-02 11:30:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:36] Number of windows considered: 1...
[2021-11-02 11:30:36] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:36] Done.
Validation 19, 3 remaining
[2021-11-02 11:30:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:37] Number of windows considered: 1...
[2021-11-02 11:30:37] Bias-correcting 1 members separately...
NaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:30:38] Done.
Validation 20, 2 remaining
[2021-11-02 11:30:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:39] Number of windows considered: 1...
[2021-11-02 11:30:39] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:39] Done.
Validation 21, 1 remaining
[2021-11-02 11:30:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:40] Number of windows considered: 1...
[2021-11-02 11:30:40] Bias-correcting 1 members separately...
NaNs producedNaNs producedno non-missing arguments to min; returning Infno non-missing arguments to max; returning -Inf[2021-11-02 11:30:40] Done.
Validation 22, 0 remaining
[2021-11-02 11:30:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:42] Number of windows considered: 1...
[2021-11-02 11:30:42] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:30:42] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-11-02 11:30:42] Performing annual aggregation...
[2021-11-02 11:30:42] Done.
[2021-11-02 11:30:42] - Computing climatology...
[2021-11-02 11:30:42] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm.cl5 <- index.cal.station.cl5
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:30:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:44] Number of windows considered: 1...
[2021-11-02 11:30:44] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:44] Done.
Validation 2, 20 remaining
[2021-11-02 11:30:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:45] Number of windows considered: 1...
[2021-11-02 11:30:45] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:45] Done.
Validation 3, 19 remaining
[2021-11-02 11:30:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:47] Number of windows considered: 1...
[2021-11-02 11:30:47] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:47] Done.
Validation 4, 18 remaining
[2021-11-02 11:30:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:48] Number of windows considered: 1...
[2021-11-02 11:30:48] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:48] Done.
Validation 5, 17 remaining
[2021-11-02 11:30:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:49] Number of windows considered: 1...
[2021-11-02 11:30:49] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:49] Done.
Validation 6, 16 remaining
[2021-11-02 11:30:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:50] Number of windows considered: 1...
[2021-11-02 11:30:50] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:50] Done.
Validation 7, 15 remaining
[2021-11-02 11:30:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:51] Number of windows considered: 1...
[2021-11-02 11:30:51] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:51] Done.
Validation 8, 14 remaining
[2021-11-02 11:30:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:52] Number of windows considered: 1...
[2021-11-02 11:30:52] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:52] Done.
Validation 9, 13 remaining
[2021-11-02 11:30:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:53] Number of windows considered: 1...
[2021-11-02 11:30:53] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:53] Done.
Validation 10, 12 remaining
[2021-11-02 11:30:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:54] Number of windows considered: 1...
[2021-11-02 11:30:54] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:54] Done.
Validation 11, 11 remaining
[2021-11-02 11:30:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:55] Number of windows considered: 1...
[2021-11-02 11:30:55] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:55] Done.
Validation 12, 10 remaining
[2021-11-02 11:30:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:56] Number of windows considered: 1...
[2021-11-02 11:30:56] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:56] Done.
Validation 13, 9 remaining
[2021-11-02 11:30:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:57] Number of windows considered: 1...
[2021-11-02 11:30:57] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:57] Done.
Validation 14, 8 remaining
[2021-11-02 11:30:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:58] Number of windows considered: 1...
[2021-11-02 11:30:58] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:58] Done.
Validation 15, 7 remaining
[2021-11-02 11:30:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:30:59] Number of windows considered: 1...
[2021-11-02 11:30:59] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:30:59] Done.
Validation 16, 6 remaining
[2021-11-02 11:31:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:00] Number of windows considered: 1...
[2021-11-02 11:31:00] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:31:00] Done.
Validation 17, 5 remaining
[2021-11-02 11:31:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:01] Number of windows considered: 1...
[2021-11-02 11:31:01] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:31:01] Done.
Validation 18, 4 remaining
[2021-11-02 11:31:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:02] Number of windows considered: 1...
[2021-11-02 11:31:02] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:31:02] Done.
Validation 19, 3 remaining
[2021-11-02 11:31:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:03] Number of windows considered: 1...
[2021-11-02 11:31:03] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:31:03] Done.
Validation 20, 2 remaining
[2021-11-02 11:31:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:04] Number of windows considered: 1...
[2021-11-02 11:31:04] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:31:04] Done.
Validation 21, 1 remaining
[2021-11-02 11:31:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:05] Number of windows considered: 1...
[2021-11-02 11:31:05] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:31:05] Done.
Validation 22, 0 remaining
[2021-11-02 11:31:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:06] Number of windows considered: 1...
[2021-11-02 11:31:06] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:31:06] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))
cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")
index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))
index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)
[2021-11-02 11:31:07] Performing annual aggregation...
[2021-11-02 11:31:07] Done.
[2021-11-02 11:31:07] - Computing climatology...
[2021-11-02 11:31:07] - Done.
index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)
index.cal.station.gpqm2.cl5 <- index.cal.station.cl5
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
EQM-WT5 GPQM2-WT5 PQM-WT5 GPQM-WT5
0.9332615 0.4444706 0.4340220 0.2609828
scores.st7.wt5 <- scores
Complete period (WO WTs)
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
[2021-11-02 11:31:07] Performing annual aggregation...
[2021-11-02 11:31:07] Done.
[2021-11-02 11:31:07] - Computing climatology...
[2021-11-02 11:31:07] - Done.
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)
index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
[2021-11-02 11:31:07] Performing annual aggregation...
[2021-11-02 11:31:07] Done.
[2021-11-02 11:31:07] - Computing climatology...
[2021-11-02 11:31:07] - Done.
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "pqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-11-02 11:31:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:09] Number of windows considered: 1...
[2021-11-02 11:31:09] Bias-correcting 1 members separately...
[2021-11-02 11:31:09] Done.
Validation 2, 20 remaining
[2021-11-02 11:31:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:10] Number of windows considered: 1...
[2021-11-02 11:31:10] Bias-correcting 1 members separately...
[2021-11-02 11:31:10] Done.
Validation 3, 19 remaining
[2021-11-02 11:31:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:10] Number of windows considered: 1...
[2021-11-02 11:31:10] Bias-correcting 1 members separately...
[2021-11-02 11:31:11] Done.
Validation 4, 18 remaining
[2021-11-02 11:31:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:11] Number of windows considered: 1...
[2021-11-02 11:31:11] Bias-correcting 1 members separately...
[2021-11-02 11:31:11] Done.
Validation 5, 17 remaining
[2021-11-02 11:31:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:12] Number of windows considered: 1...
[2021-11-02 11:31:12] Bias-correcting 1 members separately...
[2021-11-02 11:31:12] Done.
Validation 6, 16 remaining
[2021-11-02 11:31:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:13] Number of windows considered: 1...
[2021-11-02 11:31:13] Bias-correcting 1 members separately...
[2021-11-02 11:31:13] Done.
Validation 7, 15 remaining
[2021-11-02 11:31:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:14] Number of windows considered: 1...
[2021-11-02 11:31:14] Bias-correcting 1 members separately...
[2021-11-02 11:31:14] Done.
Validation 8, 14 remaining
[2021-11-02 11:31:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:15] Number of windows considered: 1...
[2021-11-02 11:31:15] Bias-correcting 1 members separately...
[2021-11-02 11:31:15] Done.
Validation 9, 13 remaining
[2021-11-02 11:31:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:16] Number of windows considered: 1...
[2021-11-02 11:31:16] Bias-correcting 1 members separately...
[2021-11-02 11:31:16] Done.
Validation 10, 12 remaining
[2021-11-02 11:31:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:17] Number of windows considered: 1...
[2021-11-02 11:31:17] Bias-correcting 1 members separately...
[2021-11-02 11:31:17] Done.
Validation 11, 11 remaining
[2021-11-02 11:31:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:18] Number of windows considered: 1...
[2021-11-02 11:31:18] Bias-correcting 1 members separately...
[2021-11-02 11:31:18] Done.
Validation 12, 10 remaining
[2021-11-02 11:31:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:19] Number of windows considered: 1...
[2021-11-02 11:31:19] Bias-correcting 1 members separately...
[2021-11-02 11:31:20] Done.
Validation 13, 9 remaining
[2021-11-02 11:31:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:20] Number of windows considered: 1...
[2021-11-02 11:31:20] Bias-correcting 1 members separately...
[2021-11-02 11:31:21] Done.
Validation 14, 8 remaining
[2021-11-02 11:31:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:22] Number of windows considered: 1...
[2021-11-02 11:31:22] Bias-correcting 1 members separately...
[2021-11-02 11:31:22] Done.
Validation 15, 7 remaining
[2021-11-02 11:31:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:23] Number of windows considered: 1...
[2021-11-02 11:31:23] Bias-correcting 1 members separately...
[2021-11-02 11:31:23] Done.
Validation 16, 6 remaining
[2021-11-02 11:31:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:24] Number of windows considered: 1...
[2021-11-02 11:31:24] Bias-correcting 1 members separately...
[2021-11-02 11:31:24] Done.
Validation 17, 5 remaining
[2021-11-02 11:31:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:25] Number of windows considered: 1...
[2021-11-02 11:31:25] Bias-correcting 1 members separately...
[2021-11-02 11:31:25] Done.
Validation 18, 4 remaining
[2021-11-02 11:31:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:27] Number of windows considered: 1...
[2021-11-02 11:31:27] Bias-correcting 1 members separately...
[2021-11-02 11:31:27] Done.
Validation 19, 3 remaining
[2021-11-02 11:31:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:28] Number of windows considered: 1...
[2021-11-02 11:31:28] Bias-correcting 1 members separately...
[2021-11-02 11:31:28] Done.
Validation 20, 2 remaining
[2021-11-02 11:31:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:29] Number of windows considered: 1...
[2021-11-02 11:31:29] Bias-correcting 1 members separately...
[2021-11-02 11:31:29] Done.
Validation 21, 1 remaining
[2021-11-02 11:31:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:30] Number of windows considered: 1...
[2021-11-02 11:31:30] Bias-correcting 1 members separately...
[2021-11-02 11:31:30] Done.
Validation 22, 0 remaining
[2021-11-02 11:31:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:31] Number of windows considered: 1...
[2021-11-02 11:31:31] Bias-correcting 1 members separately...
[2021-11-02 11:31:31] Done.
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 11:31:32] Performing annual aggregation...
[2021-11-02 11:31:32] Done.
[2021-11-02 11:31:32] - Computing climatology...
[2021-11-02 11:31:32] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.pqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "eqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-11-02 11:31:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:33] Number of windows considered: 1...
[2021-11-02 11:31:33] Bias-correcting 1 members separately...
[2021-11-02 11:31:33] Done.
Validation 2, 20 remaining
[2021-11-02 11:31:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:35] Number of windows considered: 1...
[2021-11-02 11:31:35] Bias-correcting 1 members separately...
[2021-11-02 11:31:35] Done.
Validation 3, 19 remaining
[2021-11-02 11:31:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:36] Number of windows considered: 1...
[2021-11-02 11:31:36] Bias-correcting 1 members separately...
[2021-11-02 11:31:36] Done.
Validation 4, 18 remaining
[2021-11-02 11:31:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:37] Number of windows considered: 1...
[2021-11-02 11:31:37] Bias-correcting 1 members separately...
[2021-11-02 11:31:37] Done.
Validation 5, 17 remaining
[2021-11-02 11:31:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:38] Number of windows considered: 1...
[2021-11-02 11:31:38] Bias-correcting 1 members separately...
[2021-11-02 11:31:38] Done.
Validation 6, 16 remaining
[2021-11-02 11:31:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:39] Number of windows considered: 1...
[2021-11-02 11:31:39] Bias-correcting 1 members separately...
[2021-11-02 11:31:39] Done.
Validation 7, 15 remaining
[2021-11-02 11:31:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:40] Number of windows considered: 1...
[2021-11-02 11:31:40] Bias-correcting 1 members separately...
[2021-11-02 11:31:40] Done.
Validation 8, 14 remaining
[2021-11-02 11:31:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:42] Number of windows considered: 1...
[2021-11-02 11:31:42] Bias-correcting 1 members separately...
[2021-11-02 11:31:42] Done.
Validation 9, 13 remaining
[2021-11-02 11:31:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:43] Number of windows considered: 1...
[2021-11-02 11:31:43] Bias-correcting 1 members separately...
[2021-11-02 11:31:43] Done.
Validation 10, 12 remaining
[2021-11-02 11:31:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:44] Number of windows considered: 1...
[2021-11-02 11:31:44] Bias-correcting 1 members separately...
[2021-11-02 11:31:44] Done.
Validation 11, 11 remaining
[2021-11-02 11:31:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:45] Number of windows considered: 1...
[2021-11-02 11:31:45] Bias-correcting 1 members separately...
[2021-11-02 11:31:45] Done.
Validation 12, 10 remaining
[2021-11-02 11:31:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:46] Number of windows considered: 1...
[2021-11-02 11:31:46] Bias-correcting 1 members separately...
[2021-11-02 11:31:47] Done.
Validation 13, 9 remaining
[2021-11-02 11:31:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:48] Number of windows considered: 1...
[2021-11-02 11:31:48] Bias-correcting 1 members separately...
[2021-11-02 11:31:48] Done.
Validation 14, 8 remaining
[2021-11-02 11:31:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:49] Number of windows considered: 1...
[2021-11-02 11:31:49] Bias-correcting 1 members separately...
[2021-11-02 11:31:49] Done.
Validation 15, 7 remaining
[2021-11-02 11:31:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:50] Number of windows considered: 1...
[2021-11-02 11:31:50] Bias-correcting 1 members separately...
[2021-11-02 11:31:50] Done.
Validation 16, 6 remaining
[2021-11-02 11:31:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:51] Number of windows considered: 1...
[2021-11-02 11:31:51] Bias-correcting 1 members separately...
[2021-11-02 11:31:51] Done.
Validation 17, 5 remaining
[2021-11-02 11:31:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:53] Number of windows considered: 1...
[2021-11-02 11:31:53] Bias-correcting 1 members separately...
[2021-11-02 11:31:53] Done.
Validation 18, 4 remaining
[2021-11-02 11:31:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:54] Number of windows considered: 1...
[2021-11-02 11:31:54] Bias-correcting 1 members separately...
[2021-11-02 11:31:55] Done.
Validation 19, 3 remaining
[2021-11-02 11:31:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:56] Number of windows considered: 1...
[2021-11-02 11:31:57] Bias-correcting 1 members separately...
[2021-11-02 11:31:57] Done.
Validation 20, 2 remaining
[2021-11-02 11:31:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:31:59] Number of windows considered: 1...
[2021-11-02 11:31:59] Bias-correcting 1 members separately...
[2021-11-02 11:31:59] Done.
Validation 21, 1 remaining
[2021-11-02 11:32:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:02] Number of windows considered: 1...
[2021-11-02 11:32:02] Bias-correcting 1 members separately...
[2021-11-02 11:32:02] Done.
Validation 22, 0 remaining
[2021-11-02 11:32:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:04] Number of windows considered: 1...
[2021-11-02 11:32:04] Bias-correcting 1 members separately...
[2021-11-02 11:32:05] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 11:32:06] Performing annual aggregation...
[2021-11-02 11:32:06] Done.
[2021-11-02 11:32:06] - Computing climatology...
[2021-11-02 11:32:06] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.eqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", cross.val = 'loo')
Validation 1, 21 remaining
[2021-11-02 11:32:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:09] Number of windows considered: 1...
[2021-11-02 11:32:09] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:32:10] Done.
Validation 2, 20 remaining
[2021-11-02 11:32:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:12] Number of windows considered: 1...
[2021-11-02 11:32:12] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:32:13] Done.
Validation 3, 19 remaining
[2021-11-02 11:32:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:15] Number of windows considered: 1...
[2021-11-02 11:32:15] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:32:15] Done.
Validation 4, 18 remaining
[2021-11-02 11:32:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:18] Number of windows considered: 1...
[2021-11-02 11:32:18] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:32:18] Done.
Validation 5, 17 remaining
[2021-11-02 11:32:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:21] Number of windows considered: 1...
[2021-11-02 11:32:21] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:32:21] Done.
Validation 6, 16 remaining
[2021-11-02 11:32:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:23] Number of windows considered: 1...
[2021-11-02 11:32:23] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:32:24] Done.
Validation 7, 15 remaining
[2021-11-02 11:32:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:26] Number of windows considered: 1...
[2021-11-02 11:32:26] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:32:27] Done.
Validation 8, 14 remaining
[2021-11-02 11:32:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:29] Number of windows considered: 1...
[2021-11-02 11:32:29] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:32:30] Done.
Validation 9, 13 remaining
[2021-11-02 11:32:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:33] Number of windows considered: 1...
[2021-11-02 11:32:33] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:32:34] Done.
Validation 10, 12 remaining
[2021-11-02 11:32:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:36] Number of windows considered: 1...
[2021-11-02 11:32:36] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:32:36] Done.
Validation 11, 11 remaining
[2021-11-02 11:32:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:38] Number of windows considered: 1...
[2021-11-02 11:32:38] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:32:38] Done.
Validation 12, 10 remaining
[2021-11-02 11:32:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:40] Number of windows considered: 1...
[2021-11-02 11:32:40] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:32:41] Done.
Validation 13, 9 remaining
[2021-11-02 11:32:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:43] Number of windows considered: 1...
[2021-11-02 11:32:43] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:32:43] Done.
Validation 14, 8 remaining
[2021-11-02 11:32:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:46] Number of windows considered: 1...
[2021-11-02 11:32:46] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:32:46] Done.
Validation 15, 7 remaining
[2021-11-02 11:32:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:49] Number of windows considered: 1...
[2021-11-02 11:32:49] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:32:49] Done.
Validation 16, 6 remaining
[2021-11-02 11:32:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:52] Number of windows considered: 1...
[2021-11-02 11:32:52] Bias-correcting 1 members separately...
NaNs producedNaNs producedNaNs produced[2021-11-02 11:32:52] Done.
Validation 17, 5 remaining
[2021-11-02 11:32:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:54] Number of windows considered: 1...
[2021-11-02 11:32:54] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:32:54] Done.
Validation 18, 4 remaining
[2021-11-02 11:32:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:56] Number of windows considered: 1...
[2021-11-02 11:32:56] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:32:56] Done.
Validation 19, 3 remaining
[2021-11-02 11:32:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:57] Number of windows considered: 1...
[2021-11-02 11:32:57] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:32:58] Done.
Validation 20, 2 remaining
[2021-11-02 11:32:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:32:59] Number of windows considered: 1...
[2021-11-02 11:32:59] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:32:59] Done.
Validation 21, 1 remaining
[2021-11-02 11:33:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:00] Number of windows considered: 1...
[2021-11-02 11:33:00] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:33:01] Done.
Validation 22, 0 remaining
[2021-11-02 11:33:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:02] Number of windows considered: 1...
[2021-11-02 11:33:02] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:33:02] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 11:33:03] Performing annual aggregation...
[2021-11-02 11:33:03] Done.
[2021-11-02 11:33:03] - Computing climatology...
[2021-11-02 11:33:03] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm.complete <- index.cal.station.complete
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "gpqm", theta = .7, cross.val = 'loo')
Validation 1, 21 remaining
[2021-11-02 11:33:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:04] Number of windows considered: 1...
[2021-11-02 11:33:04] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:33:05] Done.
Validation 2, 20 remaining
[2021-11-02 11:33:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:06] Number of windows considered: 1...
[2021-11-02 11:33:06] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:33:06] Done.
Validation 3, 19 remaining
[2021-11-02 11:33:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:07] Number of windows considered: 1...
[2021-11-02 11:33:07] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:33:08] Done.
Validation 4, 18 remaining
[2021-11-02 11:33:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:09] Number of windows considered: 1...
[2021-11-02 11:33:09] Bias-correcting 1 members separately...
[2021-11-02 11:33:09] Done.
Validation 5, 17 remaining
[2021-11-02 11:33:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:10] Number of windows considered: 1...
[2021-11-02 11:33:10] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:33:11] Done.
Validation 6, 16 remaining
[2021-11-02 11:33:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:12] Number of windows considered: 1...
[2021-11-02 11:33:12] Bias-correcting 1 members separately...
[2021-11-02 11:33:12] Done.
Validation 7, 15 remaining
[2021-11-02 11:33:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:13] Number of windows considered: 1...
[2021-11-02 11:33:13] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:33:13] Done.
Validation 8, 14 remaining
[2021-11-02 11:33:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:15] Number of windows considered: 1...
[2021-11-02 11:33:15] Bias-correcting 1 members separately...
[2021-11-02 11:33:15] Done.
Validation 9, 13 remaining
[2021-11-02 11:33:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:16] Number of windows considered: 1...
[2021-11-02 11:33:16] Bias-correcting 1 members separately...
[2021-11-02 11:33:17] Done.
Validation 10, 12 remaining
[2021-11-02 11:33:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:18] Number of windows considered: 1...
[2021-11-02 11:33:18] Bias-correcting 1 members separately...
[2021-11-02 11:33:18] Done.
Validation 11, 11 remaining
[2021-11-02 11:33:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:19] Number of windows considered: 1...
[2021-11-02 11:33:19] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:33:19] Done.
Validation 12, 10 remaining
[2021-11-02 11:33:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:21] Number of windows considered: 1...
[2021-11-02 11:33:21] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:33:22] Done.
Validation 13, 9 remaining
[2021-11-02 11:33:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:23] Number of windows considered: 1...
[2021-11-02 11:33:23] Bias-correcting 1 members separately...
[2021-11-02 11:33:23] Done.
Validation 14, 8 remaining
[2021-11-02 11:33:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:25] Number of windows considered: 1...
[2021-11-02 11:33:25] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:33:25] Done.
Validation 15, 7 remaining
[2021-11-02 11:33:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:27] Number of windows considered: 1...
[2021-11-02 11:33:27] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:33:27] Done.
Validation 16, 6 remaining
[2021-11-02 11:33:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:28] Number of windows considered: 1...
[2021-11-02 11:33:28] Bias-correcting 1 members separately...
NaNs producedNaNs produced[2021-11-02 11:33:28] Done.
Validation 17, 5 remaining
[2021-11-02 11:33:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:30] Number of windows considered: 1...
[2021-11-02 11:33:30] Bias-correcting 1 members separately...
[2021-11-02 11:33:30] Done.
Validation 18, 4 remaining
[2021-11-02 11:33:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:31] Number of windows considered: 1...
[2021-11-02 11:33:31] Bias-correcting 1 members separately...
[2021-11-02 11:33:32] Done.
Validation 19, 3 remaining
[2021-11-02 11:33:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:33] Number of windows considered: 1...
[2021-11-02 11:33:33] Bias-correcting 1 members separately...
[2021-11-02 11:33:34] Done.
Validation 20, 2 remaining
[2021-11-02 11:33:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:35] Number of windows considered: 1...
[2021-11-02 11:33:35] Bias-correcting 1 members separately...
[2021-11-02 11:33:36] Done.
Validation 21, 1 remaining
[2021-11-02 11:33:37] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:37] Number of windows considered: 1...
[2021-11-02 11:33:37] Bias-correcting 1 members separately...
[2021-11-02 11:33:37] Done.
Validation 22, 0 remaining
[2021-11-02 11:33:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:38] Number of windows considered: 1...
[2021-11-02 11:33:38] Bias-correcting 1 members separately...
NaNs produced[2021-11-02 11:33:38] Done.
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))
cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 11:33:39] Performing annual aggregation...
[2021-11-02 11:33:39] Done.
[2021-11-02 11:33:39] - Computing climatology...
[2021-11-02 11:33:39] - Done.
index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)
index.cal.station.gpqm2.complete <- index.cal.station.complete
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
PQM-C EQM-C TRMM GPQM-C GPQM2-C
0.7873263 0.5866852 0.4682503 0.4549036 0.3857849
scores.complete <- scores
paste(names(scores.st7.wt1[1]),names(scores.st7.wt2[1]),names(scores.st7.wt3[1]),names(scores.st7.wt4[1]),names(scores.st7.wt5[1]), names(scores.complete[1]))
[1] "PQM-WT1 EQM-WT2 PQM-WT3 EQM-WT4 EQM-WT5 PQM-C"
Combination of techniques by WT
cal.station.cl1.pqm <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE, method = "pqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:33:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:41] Number of windows considered: 1...
[2021-11-02 11:33:41] Bias-correcting 1 members separately...
[2021-11-02 11:33:41] Done.
Validation 2, 20 remaining
[2021-11-02 11:33:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:42] Number of windows considered: 1...
[2021-11-02 11:33:42] Bias-correcting 1 members separately...
[2021-11-02 11:33:42] Done.
Validation 3, 19 remaining
[2021-11-02 11:33:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:43] Number of windows considered: 1...
[2021-11-02 11:33:43] Bias-correcting 1 members separately...
[2021-11-02 11:33:43] Done.
Validation 4, 18 remaining
[2021-11-02 11:33:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:45] Number of windows considered: 1...
[2021-11-02 11:33:45] Bias-correcting 1 members separately...
[2021-11-02 11:33:45] Done.
Validation 5, 17 remaining
[2021-11-02 11:33:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:46] Number of windows considered: 1...
[2021-11-02 11:33:46] Bias-correcting 1 members separately...
[2021-11-02 11:33:46] Done.
Validation 6, 16 remaining
[2021-11-02 11:33:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:47] Number of windows considered: 1...
[2021-11-02 11:33:47] Bias-correcting 1 members separately...
[2021-11-02 11:33:47] Done.
Validation 7, 15 remaining
[2021-11-02 11:33:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:48] Number of windows considered: 1...
[2021-11-02 11:33:48] Bias-correcting 1 members separately...
[2021-11-02 11:33:48] Done.
Validation 8, 14 remaining
[2021-11-02 11:33:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:50] Number of windows considered: 1...
[2021-11-02 11:33:50] Bias-correcting 1 members separately...
[2021-11-02 11:33:50] Done.
Validation 9, 13 remaining
[2021-11-02 11:33:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:51] Number of windows considered: 1...
[2021-11-02 11:33:51] Bias-correcting 1 members separately...
[2021-11-02 11:33:51] Done.
Validation 10, 12 remaining
[2021-11-02 11:33:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:52] Number of windows considered: 1...
[2021-11-02 11:33:52] Bias-correcting 1 members separately...
[2021-11-02 11:33:52] Done.
Validation 11, 11 remaining
[2021-11-02 11:33:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:53] Number of windows considered: 1...
[2021-11-02 11:33:53] Bias-correcting 1 members separately...
[2021-11-02 11:33:53] Done.
Validation 12, 10 remaining
[2021-11-02 11:33:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:54] Number of windows considered: 1...
[2021-11-02 11:33:54] Bias-correcting 1 members separately...
[2021-11-02 11:33:54] Done.
Validation 13, 9 remaining
[2021-11-02 11:33:56] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:56] Number of windows considered: 1...
[2021-11-02 11:33:56] Bias-correcting 1 members separately...
[2021-11-02 11:33:56] Done.
Validation 14, 8 remaining
[2021-11-02 11:33:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:57] Number of windows considered: 1...
[2021-11-02 11:33:57] Bias-correcting 1 members separately...
[2021-11-02 11:33:57] Done.
Validation 15, 7 remaining
[2021-11-02 11:33:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:58] Number of windows considered: 1...
[2021-11-02 11:33:58] Bias-correcting 1 members separately...
[2021-11-02 11:33:58] Done.
Validation 16, 6 remaining
[2021-11-02 11:33:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:33:59] Number of windows considered: 1...
[2021-11-02 11:33:59] Bias-correcting 1 members separately...
[2021-11-02 11:33:59] Done.
Validation 17, 5 remaining
[2021-11-02 11:34:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:01] Number of windows considered: 1...
[2021-11-02 11:34:01] Bias-correcting 1 members separately...
[2021-11-02 11:34:01] Done.
Validation 18, 4 remaining
[2021-11-02 11:34:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:02] Number of windows considered: 1...
[2021-11-02 11:34:02] Bias-correcting 1 members separately...
[2021-11-02 11:34:02] Done.
Validation 19, 3 remaining
[2021-11-02 11:34:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:04] Number of windows considered: 1...
[2021-11-02 11:34:04] Bias-correcting 1 members separately...
[2021-11-02 11:34:04] Done.
Validation 20, 2 remaining
[2021-11-02 11:34:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:05] Number of windows considered: 1...
[2021-11-02 11:34:05] Bias-correcting 1 members separately...
[2021-11-02 11:34:05] Done.
Validation 21, 1 remaining
[2021-11-02 11:34:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:07] Number of windows considered: 1...
[2021-11-02 11:34:07] Bias-correcting 1 members separately...
[2021-11-02 11:34:07] Done.
Validation 22, 0 remaining
[2021-11-02 11:34:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:08] Number of windows considered: 1...
[2021-11-02 11:34:08] Bias-correcting 1 members separately...
[2021-11-02 11:34:08] Done.
numerical expression has 4 elements: only the first usednumerical expression has 4 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl1.pqm$Dates$start <- as.POSIXct(cal.station.cl1.pqm$Dates$start,tz = "GMT")
cal.station.cl1.pqm$Dates$end <- as.POSIXct(cal.station.cl1.pqm$Dates$end,tz = "GMT")
cal.station.cl2.eqm <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE, method = "eqm", cross.val = 'loo', wt = T)
Validation 1, 21 remaining
[2021-11-02 11:34:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:10] Number of windows considered: 1...
[2021-11-02 11:34:10] Bias-correcting 1 members separately...
[2021-11-02 11:34:10] Done.
Validation 2, 20 remaining
[2021-11-02 11:34:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:12] Number of windows considered: 1...
[2021-11-02 11:34:12] Bias-correcting 1 members separately...
[2021-11-02 11:34:12] Done.
Validation 3, 19 remaining
[2021-11-02 11:34:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:13] Number of windows considered: 1...
[2021-11-02 11:34:13] Bias-correcting 1 members separately...
[2021-11-02 11:34:13] Done.
Validation 4, 18 remaining
[2021-11-02 11:34:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:14] Number of windows considered: 1...
[2021-11-02 11:34:14] Bias-correcting 1 members separately...
[2021-11-02 11:34:15] Done.
Validation 5, 17 remaining
[2021-11-02 11:34:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:16] Number of windows considered: 1...
[2021-11-02 11:34:16] Bias-correcting 1 members separately...
[2021-11-02 11:34:16] Done.
Validation 6, 16 remaining
[2021-11-02 11:34:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:17] Number of windows considered: 1...
[2021-11-02 11:34:17] Bias-correcting 1 members separately...
[2021-11-02 11:34:17] Done.
Validation 7, 15 remaining
[2021-11-02 11:34:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:18] Number of windows considered: 1...
[2021-11-02 11:34:18] Bias-correcting 1 members separately...
[2021-11-02 11:34:19] Done.
Validation 8, 14 remaining
[2021-11-02 11:34:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:20] Number of windows considered: 1...
[2021-11-02 11:34:20] Bias-correcting 1 members separately...
[2021-11-02 11:34:20] Done.
Validation 9, 13 remaining
[2021-11-02 11:34:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:21] Number of windows considered: 1...
[2021-11-02 11:34:21] Bias-correcting 1 members separately...
[2021-11-02 11:34:21] Done.
Validation 10, 12 remaining
[2021-11-02 11:34:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:23] Number of windows considered: 1...
[2021-11-02 11:34:23] Bias-correcting 1 members separately...
[2021-11-02 11:34:23] Done.
Validation 11, 11 remaining
[2021-11-02 11:34:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:24] Number of windows considered: 1...
[2021-11-02 11:34:24] Bias-correcting 1 members separately...
[2021-11-02 11:34:24] Done.
Validation 12, 10 remaining
[2021-11-02 11:34:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:26] Number of windows considered: 1...
[2021-11-02 11:34:26] Bias-correcting 1 members separately...
[2021-11-02 11:34:26] Done.
Validation 13, 9 remaining
[2021-11-02 11:34:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:27] Number of windows considered: 1...
[2021-11-02 11:34:27] Bias-correcting 1 members separately...
[2021-11-02 11:34:27] Done.
Validation 14, 8 remaining
[2021-11-02 11:34:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:28] Number of windows considered: 1...
[2021-11-02 11:34:28] Bias-correcting 1 members separately...
[2021-11-02 11:34:28] Done.
Validation 15, 7 remaining
[2021-11-02 11:34:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:30] Number of windows considered: 1...
[2021-11-02 11:34:30] Bias-correcting 1 members separately...
[2021-11-02 11:34:30] Done.
Validation 16, 6 remaining
[2021-11-02 11:34:31] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:31] Number of windows considered: 1...
[2021-11-02 11:34:31] Bias-correcting 1 members separately...
[2021-11-02 11:34:31] Done.
Validation 17, 5 remaining
[2021-11-02 11:34:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:33] Number of windows considered: 1...
[2021-11-02 11:34:33] Bias-correcting 1 members separately...
[2021-11-02 11:34:33] Done.
Validation 18, 4 remaining
[2021-11-02 11:34:34] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:34] Number of windows considered: 1...
[2021-11-02 11:34:34] Bias-correcting 1 members separately...
[2021-11-02 11:34:35] Done.
Validation 19, 3 remaining
[2021-11-02 11:34:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:36] Number of windows considered: 1...
[2021-11-02 11:34:36] Bias-correcting 1 members separately...
[2021-11-02 11:34:36] Done.
Validation 20, 2 remaining
[2021-11-02 11:34:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:38] Number of windows considered: 1...
[2021-11-02 11:34:38] Bias-correcting 1 members separately...
[2021-11-02 11:34:38] Done.
Validation 21, 1 remaining
[2021-11-02 11:34:39] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:39] Number of windows considered: 1...
[2021-11-02 11:34:39] Bias-correcting 1 members separately...
[2021-11-02 11:34:39] Done.
Validation 22, 0 remaining
[2021-11-02 11:34:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:40] Number of windows considered: 1...
[2021-11-02 11:34:40] Bias-correcting 1 members separately...
[2021-11-02 11:34:40] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl2.eqm$Dates$start <- as.POSIXct(cal.station.cl2.eqm$Dates$start,tz = "GMT")
cal.station.cl2.eqm$Dates$end <- as.POSIXct(cal.station.cl2.eqm$Dates$end,tz = "GMT")
cal.station.cl3.pqm <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE, method = "pqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-11-02 11:34:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:42] Number of windows considered: 1...
[2021-11-02 11:34:42] Bias-correcting 1 members separately...
[2021-11-02 11:34:42] Done.
Validation 2, 20 remaining
[2021-11-02 11:34:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:43] Number of windows considered: 1...
[2021-11-02 11:34:43] Bias-correcting 1 members separately...
[2021-11-02 11:34:43] Done.
Validation 3, 19 remaining
[2021-11-02 11:34:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:44] Number of windows considered: 1...
[2021-11-02 11:34:44] Bias-correcting 1 members separately...
[2021-11-02 11:34:44] Done.
Validation 4, 18 remaining
[2021-11-02 11:34:45] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:45] Number of windows considered: 1...
[2021-11-02 11:34:45] Bias-correcting 1 members separately...
[2021-11-02 11:34:45] Done.
Validation 5, 17 remaining
[2021-11-02 11:34:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:46] Number of windows considered: 1...
[2021-11-02 11:34:46] Bias-correcting 1 members separately...
[2021-11-02 11:34:46] Done.
Validation 6, 16 remaining
[2021-11-02 11:34:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:47] Number of windows considered: 1...
[2021-11-02 11:34:47] Bias-correcting 1 members separately...
[2021-11-02 11:34:47] Done.
Validation 7, 15 remaining
[2021-11-02 11:34:48] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:48] Number of windows considered: 1...
[2021-11-02 11:34:48] Bias-correcting 1 members separately...
[2021-11-02 11:34:48] Done.
Validation 8, 14 remaining
[2021-11-02 11:34:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:49] Number of windows considered: 1...
[2021-11-02 11:34:49] Bias-correcting 1 members separately...
[2021-11-02 11:34:49] Done.
Validation 9, 13 remaining
[2021-11-02 11:34:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:50] Number of windows considered: 1...
[2021-11-02 11:34:50] Bias-correcting 1 members separately...
[2021-11-02 11:34:50] Done.
Validation 10, 12 remaining
[2021-11-02 11:34:51] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:51] Number of windows considered: 1...
[2021-11-02 11:34:51] Bias-correcting 1 members separately...
[2021-11-02 11:34:51] Done.
Validation 11, 11 remaining
[2021-11-02 11:34:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:52] Number of windows considered: 1...
[2021-11-02 11:34:52] Bias-correcting 1 members separately...
[2021-11-02 11:34:52] Done.
Validation 12, 10 remaining
[2021-11-02 11:34:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:53] Number of windows considered: 1...
[2021-11-02 11:34:53] Bias-correcting 1 members separately...
[2021-11-02 11:34:53] Done.
Validation 13, 9 remaining
[2021-11-02 11:34:54] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:54] Number of windows considered: 1...
[2021-11-02 11:34:54] Bias-correcting 1 members separately...
[2021-11-02 11:34:54] Done.
Validation 14, 8 remaining
[2021-11-02 11:34:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:55] Number of windows considered: 1...
[2021-11-02 11:34:55] Bias-correcting 1 members separately...
[2021-11-02 11:34:56] Done.
Validation 15, 7 remaining
[2021-11-02 11:34:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:57] Number of windows considered: 1...
[2021-11-02 11:34:57] Bias-correcting 1 members separately...
[2021-11-02 11:34:57] Done.
Validation 16, 6 remaining
[2021-11-02 11:34:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:58] Number of windows considered: 1...
[2021-11-02 11:34:58] Bias-correcting 1 members separately...
[2021-11-02 11:34:58] Done.
Validation 17, 5 remaining
[2021-11-02 11:34:59] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:34:59] Number of windows considered: 1...
[2021-11-02 11:34:59] Bias-correcting 1 members separately...
[2021-11-02 11:34:59] Done.
Validation 18, 4 remaining
[2021-11-02 11:35:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:00] Number of windows considered: 1...
[2021-11-02 11:35:00] Bias-correcting 1 members separately...
[2021-11-02 11:35:00] Done.
Validation 19, 3 remaining
[2021-11-02 11:35:01] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:01] Number of windows considered: 1...
[2021-11-02 11:35:01] Bias-correcting 1 members separately...
[2021-11-02 11:35:01] Done.
Validation 20, 2 remaining
[2021-11-02 11:35:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:02] Number of windows considered: 1...
[2021-11-02 11:35:02] Bias-correcting 1 members separately...
[2021-11-02 11:35:02] Done.
Validation 21, 1 remaining
[2021-11-02 11:35:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:03] Number of windows considered: 1...
[2021-11-02 11:35:03] Bias-correcting 1 members separately...
[2021-11-02 11:35:03] Done.
Validation 22, 0 remaining
[2021-11-02 11:35:04] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:04] Number of windows considered: 1...
[2021-11-02 11:35:04] Bias-correcting 1 members separately...
[2021-11-02 11:35:04] Done.
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl3.pqm$Dates$start <- as.POSIXct(cal.station.cl3.pqm$Dates$start,tz = "GMT")
cal.station.cl3.pqm$Dates$end <- as.POSIXct(cal.station.cl3.pqm$Dates$end,tz = "GMT")
cal.station.cl4.eqm <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE, method = "eqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-11-02 11:35:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:05] Number of windows considered: 1...
[2021-11-02 11:35:05] Bias-correcting 1 members separately...
[2021-11-02 11:35:05] Done.
Validation 2, 20 remaining
[2021-11-02 11:35:07] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:07] Number of windows considered: 1...
[2021-11-02 11:35:07] Bias-correcting 1 members separately...
[2021-11-02 11:35:07] Done.
Validation 3, 19 remaining
[2021-11-02 11:35:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:08] Number of windows considered: 1...
[2021-11-02 11:35:08] Bias-correcting 1 members separately...
[2021-11-02 11:35:08] Done.
Validation 4, 18 remaining
[2021-11-02 11:35:09] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:09] Number of windows considered: 1...
[2021-11-02 11:35:09] Bias-correcting 1 members separately...
[2021-11-02 11:35:09] Done.
Validation 5, 17 remaining
[2021-11-02 11:35:10] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:10] Number of windows considered: 1...
[2021-11-02 11:35:10] Bias-correcting 1 members separately...
[2021-11-02 11:35:10] Done.
Validation 6, 16 remaining
[2021-11-02 11:35:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:11] Number of windows considered: 1...
[2021-11-02 11:35:11] Bias-correcting 1 members separately...
[2021-11-02 11:35:11] Done.
Validation 7, 15 remaining
[2021-11-02 11:35:12] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:12] Number of windows considered: 1...
[2021-11-02 11:35:12] Bias-correcting 1 members separately...
[2021-11-02 11:35:12] Done.
Validation 8, 14 remaining
[2021-11-02 11:35:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:14] Number of windows considered: 1...
[2021-11-02 11:35:14] Bias-correcting 1 members separately...
[2021-11-02 11:35:14] Done.
Validation 9, 13 remaining
[2021-11-02 11:35:15] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:15] Number of windows considered: 1...
[2021-11-02 11:35:15] Bias-correcting 1 members separately...
[2021-11-02 11:35:15] Done.
Validation 10, 12 remaining
[2021-11-02 11:35:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:16] Number of windows considered: 1...
[2021-11-02 11:35:16] Bias-correcting 1 members separately...
[2021-11-02 11:35:16] Done.
Validation 11, 11 remaining
[2021-11-02 11:35:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:17] Number of windows considered: 1...
[2021-11-02 11:35:17] Bias-correcting 1 members separately...
[2021-11-02 11:35:17] Done.
Validation 12, 10 remaining
[2021-11-02 11:35:18] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:18] Number of windows considered: 1...
[2021-11-02 11:35:18] Bias-correcting 1 members separately...
[2021-11-02 11:35:19] Done.
Validation 13, 9 remaining
[2021-11-02 11:35:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:20] Number of windows considered: 1...
[2021-11-02 11:35:20] Bias-correcting 1 members separately...
[2021-11-02 11:35:20] Done.
Validation 14, 8 remaining
[2021-11-02 11:35:21] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:21] Number of windows considered: 1...
[2021-11-02 11:35:21] Bias-correcting 1 members separately...
[2021-11-02 11:35:21] Done.
Validation 15, 7 remaining
[2021-11-02 11:35:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:22] Number of windows considered: 1...
[2021-11-02 11:35:22] Bias-correcting 1 members separately...
[2021-11-02 11:35:22] Done.
Validation 16, 6 remaining
[2021-11-02 11:35:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:23] Number of windows considered: 1...
[2021-11-02 11:35:23] Bias-correcting 1 members separately...
[2021-11-02 11:35:23] Done.
Validation 17, 5 remaining
[2021-11-02 11:35:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:24] Number of windows considered: 1...
[2021-11-02 11:35:24] Bias-correcting 1 members separately...
[2021-11-02 11:35:24] Done.
Validation 18, 4 remaining
[2021-11-02 11:35:25] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:26] Number of windows considered: 1...
[2021-11-02 11:35:26] Bias-correcting 1 members separately...
[2021-11-02 11:35:26] Done.
Validation 19, 3 remaining
[2021-11-02 11:35:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:27] Number of windows considered: 1...
[2021-11-02 11:35:27] Bias-correcting 1 members separately...
[2021-11-02 11:35:27] Done.
Validation 20, 2 remaining
[2021-11-02 11:35:28] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:28] Number of windows considered: 1...
[2021-11-02 11:35:28] Bias-correcting 1 members separately...
[2021-11-02 11:35:28] Done.
Validation 21, 1 remaining
[2021-11-02 11:35:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:29] Number of windows considered: 1...
[2021-11-02 11:35:29] Bias-correcting 1 members separately...
[2021-11-02 11:35:29] Done.
Validation 22, 0 remaining
[2021-11-02 11:35:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:30] Number of windows considered: 1...
[2021-11-02 11:35:30] Bias-correcting 1 members separately...
[2021-11-02 11:35:31] Done.
numerical expression has 8 elements: only the first usednumerical expression has 8 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl4.eqm$Dates$start <- as.POSIXct(cal.station.cl4.eqm$Dates$start,tz = "GMT")
cal.station.cl4.eqm$Dates$end <- as.POSIXct(cal.station.cl4.eqm$Dates$end,tz = "GMT")
cal.station.cl5.eqm <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE, method = "eqm", cross.val = "loo", wt = T)
Validation 1, 21 remaining
[2021-11-02 11:35:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:33] Number of windows considered: 1...
[2021-11-02 11:35:33] Bias-correcting 1 members separately...
[2021-11-02 11:35:34] Done.
Validation 2, 20 remaining
[2021-11-02 11:35:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:36] Number of windows considered: 1...
[2021-11-02 11:35:36] Bias-correcting 1 members separately...
[2021-11-02 11:35:36] Done.
Validation 3, 19 remaining
[2021-11-02 11:35:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:38] Number of windows considered: 1...
[2021-11-02 11:35:38] Bias-correcting 1 members separately...
[2021-11-02 11:35:38] Done.
Validation 4, 18 remaining
[2021-11-02 11:35:40] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:40] Number of windows considered: 1...
[2021-11-02 11:35:40] Bias-correcting 1 members separately...
[2021-11-02 11:35:40] Done.
Validation 5, 17 remaining
[2021-11-02 11:35:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:41] Number of windows considered: 1...
[2021-11-02 11:35:41] Bias-correcting 1 members separately...
[2021-11-02 11:35:42] Done.
Validation 6, 16 remaining
[2021-11-02 11:35:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:43] Number of windows considered: 1...
[2021-11-02 11:35:43] Bias-correcting 1 members separately...
[2021-11-02 11:35:43] Done.
Validation 7, 15 remaining
[2021-11-02 11:35:44] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:44] Number of windows considered: 1...
[2021-11-02 11:35:44] Bias-correcting 1 members separately...
[2021-11-02 11:35:44] Done.
Validation 8, 14 remaining
[2021-11-02 11:35:46] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:46] Number of windows considered: 1...
[2021-11-02 11:35:46] Bias-correcting 1 members separately...
[2021-11-02 11:35:46] Done.
Validation 9, 13 remaining
[2021-11-02 11:35:47] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:47] Number of windows considered: 1...
[2021-11-02 11:35:47] Bias-correcting 1 members separately...
[2021-11-02 11:35:47] Done.
Validation 10, 12 remaining
[2021-11-02 11:35:49] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:49] Number of windows considered: 1...
[2021-11-02 11:35:49] Bias-correcting 1 members separately...
[2021-11-02 11:35:49] Done.
Validation 11, 11 remaining
[2021-11-02 11:35:50] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:50] Number of windows considered: 1...
[2021-11-02 11:35:50] Bias-correcting 1 members separately...
[2021-11-02 11:35:50] Done.
Validation 12, 10 remaining
[2021-11-02 11:35:52] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:52] Number of windows considered: 1...
[2021-11-02 11:35:52] Bias-correcting 1 members separately...
[2021-11-02 11:35:52] Done.
Validation 13, 9 remaining
[2021-11-02 11:35:53] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:53] Number of windows considered: 1...
[2021-11-02 11:35:53] Bias-correcting 1 members separately...
[2021-11-02 11:35:53] Done.
Validation 14, 8 remaining
[2021-11-02 11:35:55] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:55] Number of windows considered: 1...
[2021-11-02 11:35:55] Bias-correcting 1 members separately...
[2021-11-02 11:35:55] Done.
Validation 15, 7 remaining
[2021-11-02 11:35:57] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:57] Number of windows considered: 1...
[2021-11-02 11:35:57] Bias-correcting 1 members separately...
[2021-11-02 11:35:57] Done.
Validation 16, 6 remaining
[2021-11-02 11:35:58] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:35:58] Number of windows considered: 1...
[2021-11-02 11:35:58] Bias-correcting 1 members separately...
[2021-11-02 11:35:58] Done.
Validation 17, 5 remaining
[2021-11-02 11:36:00] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:00] Number of windows considered: 1...
[2021-11-02 11:36:00] Bias-correcting 1 members separately...
[2021-11-02 11:36:00] Done.
Validation 18, 4 remaining
[2021-11-02 11:36:02] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:02] Number of windows considered: 1...
[2021-11-02 11:36:02] Bias-correcting 1 members separately...
[2021-11-02 11:36:02] Done.
Validation 19, 3 remaining
[2021-11-02 11:36:03] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:03] Number of windows considered: 1...
[2021-11-02 11:36:03] Bias-correcting 1 members separately...
[2021-11-02 11:36:03] Done.
Validation 20, 2 remaining
[2021-11-02 11:36:05] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:05] Number of windows considered: 1...
[2021-11-02 11:36:05] Bias-correcting 1 members separately...
[2021-11-02 11:36:05] Done.
Validation 21, 1 remaining
[2021-11-02 11:36:06] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:06] Number of windows considered: 1...
[2021-11-02 11:36:06] Bias-correcting 1 members separately...
[2021-11-02 11:36:06] Done.
Validation 22, 0 remaining
[2021-11-02 11:36:08] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:08] Number of windows considered: 1...
[2021-11-02 11:36:08] Bias-correcting 1 members separately...
[2021-11-02 11:36:08] Done.
numerical expression has 2 elements: only the first usednumerical expression has 2 elements: only the first usedNOTE: Some data will be lost on year-crossing season subset (see the 'Time slicing' section of subsetGrid documentation for more details)
#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl5.eqm$Dates$start <- as.POSIXct(cal.station.cl5.eqm$Dates$start,tz = "GMT")
cal.station.cl5.eqm$Dates$end <- as.POSIXct(cal.station.cl5.eqm$Dates$end,tz = "GMT")
idx <- which(!is.na(cal.station.cl1.pqm$Data))
cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl2.eqm$Data))
cal.station.cl2.eqm <- subsetDimension(cal.station.cl2.eqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl3.pqm$Data))
cal.station.cl3.pqm <- subsetDimension(cal.station.cl3.pqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl4.eqm$Data))
cal.station.cl4.eqm <- subsetDimension(cal.station.cl4.eqm, dimension = "time", indices = idx)
idx <- which(!is.na(cal.station.cl5.eqm$Data))
cal.station.cl5.eqm <- subsetDimension(cal.station.cl5.eqm, dimension = "time", indices = idx)
wt_conditioned <- bindGrid(cal.station.cl1.pqm, cal.station.cl2.eqm, cal.station.cl3.pqm,
cal.station.cl4.eqm, cal.station.cl5.eqm, dimension = "time")
attr(wt_conditioned$Data, "dimensions") <- "time"
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE, method = "pqm", cross.val = "loo")
Validation 1, 21 remaining
[2021-11-02 11:36:11] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:11] Number of windows considered: 1...
[2021-11-02 11:36:11] Bias-correcting 1 members separately...
[2021-11-02 11:36:11] Done.
Validation 2, 20 remaining
[2021-11-02 11:36:13] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:13] Number of windows considered: 1...
[2021-11-02 11:36:13] Bias-correcting 1 members separately...
[2021-11-02 11:36:13] Done.
Validation 3, 19 remaining
[2021-11-02 11:36:14] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:14] Number of windows considered: 1...
[2021-11-02 11:36:14] Bias-correcting 1 members separately...
[2021-11-02 11:36:14] Done.
Validation 4, 18 remaining
[2021-11-02 11:36:16] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:16] Number of windows considered: 1...
[2021-11-02 11:36:16] Bias-correcting 1 members separately...
[2021-11-02 11:36:16] Done.
Validation 5, 17 remaining
[2021-11-02 11:36:17] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:17] Number of windows considered: 1...
[2021-11-02 11:36:17] Bias-correcting 1 members separately...
[2021-11-02 11:36:18] Done.
Validation 6, 16 remaining
[2021-11-02 11:36:19] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:19] Number of windows considered: 1...
[2021-11-02 11:36:19] Bias-correcting 1 members separately...
[2021-11-02 11:36:19] Done.
Validation 7, 15 remaining
[2021-11-02 11:36:20] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:20] Number of windows considered: 1...
[2021-11-02 11:36:20] Bias-correcting 1 members separately...
[2021-11-02 11:36:20] Done.
Validation 8, 14 remaining
[2021-11-02 11:36:22] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:22] Number of windows considered: 1...
[2021-11-02 11:36:22] Bias-correcting 1 members separately...
[2021-11-02 11:36:22] Done.
Validation 9, 13 remaining
[2021-11-02 11:36:23] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:23] Number of windows considered: 1...
[2021-11-02 11:36:23] Bias-correcting 1 members separately...
[2021-11-02 11:36:23] Done.
Validation 10, 12 remaining
[2021-11-02 11:36:24] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:24] Number of windows considered: 1...
[2021-11-02 11:36:24] Bias-correcting 1 members separately...
[2021-11-02 11:36:25] Done.
Validation 11, 11 remaining
[2021-11-02 11:36:26] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:26] Number of windows considered: 1...
[2021-11-02 11:36:26] Bias-correcting 1 members separately...
[2021-11-02 11:36:26] Done.
Validation 12, 10 remaining
[2021-11-02 11:36:27] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:27] Number of windows considered: 1...
[2021-11-02 11:36:27] Bias-correcting 1 members separately...
[2021-11-02 11:36:27] Done.
Validation 13, 9 remaining
[2021-11-02 11:36:29] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:29] Number of windows considered: 1...
[2021-11-02 11:36:29] Bias-correcting 1 members separately...
[2021-11-02 11:36:29] Done.
Validation 14, 8 remaining
[2021-11-02 11:36:30] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:30] Number of windows considered: 1...
[2021-11-02 11:36:30] Bias-correcting 1 members separately...
[2021-11-02 11:36:30] Done.
Validation 15, 7 remaining
[2021-11-02 11:36:32] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:32] Number of windows considered: 1...
[2021-11-02 11:36:32] Bias-correcting 1 members separately...
[2021-11-02 11:36:32] Done.
Validation 16, 6 remaining
[2021-11-02 11:36:33] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:33] Number of windows considered: 1...
[2021-11-02 11:36:33] Bias-correcting 1 members separately...
[2021-11-02 11:36:33] Done.
Validation 17, 5 remaining
[2021-11-02 11:36:35] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:35] Number of windows considered: 1...
[2021-11-02 11:36:35] Bias-correcting 1 members separately...
[2021-11-02 11:36:35] Done.
Validation 18, 4 remaining
[2021-11-02 11:36:36] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:36] Number of windows considered: 1...
[2021-11-02 11:36:36] Bias-correcting 1 members separately...
[2021-11-02 11:36:36] Done.
Validation 19, 3 remaining
[2021-11-02 11:36:38] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:38] Number of windows considered: 1...
[2021-11-02 11:36:38] Bias-correcting 1 members separately...
[2021-11-02 11:36:38] Done.
Validation 20, 2 remaining
[2021-11-02 11:36:41] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:41] Number of windows considered: 1...
[2021-11-02 11:36:41] Bias-correcting 1 members separately...
[2021-11-02 11:36:41] Done.
Validation 21, 1 remaining
[2021-11-02 11:36:42] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:42] Number of windows considered: 1...
[2021-11-02 11:36:42] Bias-correcting 1 members separately...
[2021-11-02 11:36:42] Done.
Validation 22, 0 remaining
[2021-11-02 11:36:43] Argument precipitation is set as TRUE, please ensure that this matches your data.
[2021-11-02 11:36:43] Number of windows considered: 1...
[2021-11-02 11:36:43] Bias-correcting 1 members separately...
[2021-11-02 11:36:43] Done.
# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")
index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))
index.combinated.rv20max <- MaxReturnValue(wt_conditioned)
[2021-11-02 11:36:43] Performing annual aggregation...
[2021-11-02 11:36:43] Done.
[2021-11-02 11:36:43] - Computing climatology...
[2021-11-02 11:36:43] - Done.
index.combinated <- c(index.combinated, index.combinated.rv20max)
index.pqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.pqm <- c(index.pqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))
index.pqm.rv20max <- MaxReturnValue(cal.station.complete)
[2021-11-02 11:36:44] Performing annual aggregation...
[2021-11-02 11:36:44] Done.
[2021-11-02 11:36:44] - Computing climatology...
[2021-11-02 11:36:44] - Done.
index.pqm<- c(index.pqm ,index.pqm.rv20max)
index.pqm
Skewness SDII R10 R10p R20 R20p P98Wet
4.069597e+00 1.566435e+01 2.336321e-01 5.846373e+04 1.294498e-01 4.649161e+04 8.209916e+01
P98WetAmount RV20_max
1.060476e+04 2.004862e+02
diff.conditioned <- abs(index.obs-index.combinated)
diff.pqm <- abs(index.obs-index.pqm)
measures <- list()
for (i in c(1:9)) {
measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i]))
}
norm.vector <- list()
for (i in c(1:length(measures))) {
norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]])
}
# score.trmm <- c()
# for (i in c(1:9)) {
# score.trmm <- c(score.trmm, norm.vector[[i]][1])
# }
# score.trmm <- mean(score.trmm)
score.pqm <- c()
for (i in c(1:9)) {
score.pqm <- c(score.pqm, norm.vector[[i]][1])
}
score.pqm <- mean(score.pqm)
score.eqm <- c()
for (i in c(1:9)) {
score.eqm <- c(score.eqm, norm.vector[[i]][2])
}
score.eqm <- mean(score.eqm)
score.gpqm <- c()
for (i in c(1:9)) {
score.gpqm <- c(score.gpqm, norm.vector[[i]][3])
}
score.gpqm <- mean(score.gpqm)
score.gpqm2 <- c()
for (i in c(1:9)) {
score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4])
}
score.gpqm2 <- mean(score.gpqm2)
score.combinated <- c()
for (i in c(1:9)) {
score.combinated <- c(score.combinated, norm.vector[[i]][5])
}
score.combinated <- mean(score.combinated)
scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
Combined PQM-C EQM-C GPQM-C GPQM2-C
0.8066544 0.7714480 0.5783975 0.4417927 0.3674400
df <- data.frame(index.obs, index.combinated, index.pqm)
colnames(df) <- c("Observation","Conditioned", "PQM")
format(df, digits = 3, scientific = 5)
bias.df <- data.frame(diff.conditioned, diff.pqm)
colnames(bias.df) <- c("Bias Conditioned", "Bias PQM")
format(bias.df, digits = 3, scientific = 5)
df.st1 <- df
bias.df.st1 <- bias.df
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100
names(bias.rel.cond) <- names(diff.conditioned)
bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100
names(bias.rel.no.cond) <- names(diff.conditioned)
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)
colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias PQM")
format(bias.rel.df, digits = 3, scientific = 5)
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))
abline(a = 0, b = 1)
station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))
points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))
idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))
station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)
points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)
legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))
grid()

---
title: "Assesment of the conditioned calibration with crossvalidation"
output: 
  html_notebook:
    theme: united
    toc: yes
    toc_depth: 5
---

```{r}
library(devtools)
library(transformeR)
load_all("C:/Users/usuario/Desktop/transformeR")
load_all("C:/Users/usuario/Desktop/downscaleR")
load_all("C:/Users/usuario/Desktop/climate4R.value")
```

```{r}
library(loadeR)
library(climate4R.value)
library(magrittr)
library(evd)
library(formattable) #neccessary to create tables with colors
library(lubridate) #neccessary to calculate differences in years between dates
library(lattice)
library(abind) #necessary to biasCorrectionMod works
library(MASS) 
library(dplyr)
```




```{r}
set.seed(42)

load("C:/Users/usuario/Desktop/TRMM-Calibration/Data/pca.RData")
#load("/media/meteo/TOURO Mobile/work/TRMM-Calibration/Data/pp_reanalysis.RData")
idx.tp <- which(attributes(pca$tp[[1]])$explained_variance >= .75)[1]
idx.msl <- which(attributes(pca$msl[[1]])$explained_variance >= .9)[1]
idx.diff.msl <- which(attributes(pca$diff_msl[[1]])$explained_variance >= .9)[1]

pca.matrix <- cbind(pca$tp[[1]]$PCs[,1:idx.tp],pca$msl[[1]]$PCs[,1:idx.msl],pca$diff_msl[[1]]$PCs[,1:idx.diff.msl])

k = 5
load('C:/Users/usuario/Desktop/TRMM-Calibration/Data/kmModel5.RData')

precip_obs <- loadStationData("C:/Users/usuario/Desktop/TRMM-Calibration/Data/SP_ascii.zip", var = "precip_obs")
precip_trmm <- loadStationData("C:/Users/usuario/Desktop/TRMM-Calibration/Data/SP_ascii.zip", var = "precip_trmm")

```


```{r}
kmModel5$cluster <- kmModel5$cluster[1:8034]

```

```{r}
MaxReturnValue <- function(data){
  #library(lubridate)
  #nyears <- round(time_length(difftime(cal.madrid.eqm$Dates$end[length(cal.madrid.eqm$Dates$end)], cal.madrid.eqm$Dates$start[1]),"years"))
  nyears <- 20
  data.maxYear <- aggregateGrid(redim(data), aggr.y = list(FUN = "max",na.rm = TRUE))

  data.maxrv <- climatology(data, clim.fun = list(FUN = "mean", na.rm = T))

  auxData <- data.maxYear$Data
  auxData[which(is.infinite(auxData))] <- NA

  if (any(!is.na(auxData))){
      auxGEV <- fgev(auxData)
      if ((auxGEV$estimate[3] - auxGEV$std.err[3] < 0) & (0  < auxGEV$estimate[3] + auxGEV$std.err[3])){
        auxGEV <- fgev(auxData, shape = 0)
        auxRV <- qgev(1-1/nyears, loc = auxGEV$estimate[1], scale = auxGEV$estimate[2], shape = 0)
      }else{
        auxRV <- qgev(1-1/nyears, loc = auxGEV$estimate[1], scale = auxGEV$estimate[2], shape = auxGEV$estimate[3])
      }
      data.maxrv <- as.numeric(auxRV)
      names(data.maxrv) <- paste("RV",nyears,"_max", sep = "")
  }
  return(data.maxrv)
  }
```



## Wallis and Futuna


```{r}
i=1

station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
```


````{r}
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
index.obs <- c(index.obs, index.obs.rv20max)

index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
index.trmm <- c(index.trmm, index.trmm.rv20max)


```



### WT1

```{r}
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))


station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))


```

```{r}
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)

index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
```

```{r}
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")

station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")

cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "pqm",cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.pqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.eqm.cl1 <- index.cal.station.cl1


```

```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm2.cl1 <- index.cal.station.cl1


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i])) 
}

```

```{r}
normalization <- function(measure){
  measure.norm <- c()
  #measure must be a vector with the value of a certain measure of different calibrations
  for (i in c(1:length(measure))) {
    measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
  }
  return(measure.norm)
}
```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
```
```{r}
scores.st1.wt1 <- scores
```

### WT2
```{r}
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))


station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))

```

```{r}
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)

index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)

```

```{r}
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")

station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")

cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.pqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.eqm.cl2 <- index.cal.station.cl2


```

```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm2.cl2 <- index.cal.station.cl2


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores


```
```{r}
scores.st1.wt2 <- scores
```

### WT3

```{r}
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))


station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))

```

```{r}
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)

index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)

```

```{r}
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")

station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")

cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.pqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.eqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm2.cl3 <- index.cal.station.cl3


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)

score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st1.wt3 <- scores
```
### WT4

```{r}
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))


station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))

```

```{r}
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)

index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)


```

```{r}
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")

station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")


cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.pqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.eqm.cl4 <- index.cal.station.cl4


```

```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm2.cl4 <- index.cal.station.cl4


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)

score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st1.wt4 <- scores
```
### WT5

```{r}
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))


station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))

```

```{r}
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)

index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
```

```{r}
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")

station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")

cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.pqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.eqm.cl5 <- index.cal.station.cl5


```

```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm2.cl5 <- index.cal.station.cl5


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st1.wt5 <- scores
```




### Complete period (WO WTs)



```{r}
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)

index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
```
```{r}
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "pqm", cross.val = 'loo')

cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")

cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.pqm.complete <- index.cal.station.complete


```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "eqm", cross.val = 'loo')


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.eqm.complete <- index.cal.station.complete


```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", cross.val = "loo")


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm.complete <- index.cal.station.complete



```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", theta = .7, cross.val = "loo")


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm2.complete <- index.cal.station.complete



```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.trmm.complete[i]-index.obs.complete[i]),abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
score.trmm <- c()
for (i in c(1:9)) {
  score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
}
score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][2]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][3]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][4]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][5]) 
}
score.gpqm2 <- mean(score.gpqm2)


scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.complete <- scores
```

```{r}
paste(names(scores.st1.wt1[1]),names(scores.st1.wt2[1]),names(scores.st1.wt3[1]),names(scores.st1.wt4[1]),names(scores.st1.wt5[1]), names(scores.complete[1]))
```

### Combination of techniques by WT

```{r}
cal.station.cl1.pqm <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T ) 

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl1.pqm$Dates$start <- as.POSIXct(cal.station.cl1.pqm$Dates$start,tz = "GMT")
cal.station.cl1.pqm$Dates$end <- as.POSIXct(cal.station.cl1.pqm$Dates$end,tz = "GMT")

cal.station.cl2.pqm <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl2.pqm$Dates$start <- as.POSIXct(cal.station.cl2.pqm$Dates$start,tz = "GMT")
cal.station.cl2.pqm$Dates$end <- as.POSIXct(cal.station.cl2.pqm$Dates$end,tz = "GMT")

cal.station.cl3.pqm <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl3.pqm$Dates$start <- as.POSIXct(cal.station.cl3.pqm$Dates$start,tz = "GMT")
cal.station.cl3.pqm$Dates$end <- as.POSIXct(cal.station.cl3.pqm$Dates$end,tz = "GMT")

cal.station.cl4.gpqm2 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm", theta = .7, cross.val = 'loo', wt = T) 

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl4.gpqm2$Dates$start <- as.POSIXct(cal.station.cl4.gpqm2$Dates$start,tz = "GMT")
cal.station.cl4.gpqm2$Dates$end <- as.POSIXct(cal.station.cl4.gpqm2$Dates$end,tz = "GMT")

cal.station.cl5.pqm <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T) 

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl5.pqm$Dates$start <- as.POSIXct(cal.station.cl5.pqm$Dates$start,tz = "GMT")
cal.station.cl5.pqm$Dates$end <- as.POSIXct(cal.station.cl5.pqm$Dates$end,tz = "GMT")


idx <- which(!is.na(cal.station.cl1.pqm$Data))
cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl2.pqm$Data))
cal.station.cl2.pqm <- subsetDimension(cal.station.cl2.pqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl3.pqm$Data))
cal.station.cl3.pqm <- subsetDimension(cal.station.cl3.pqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl4.gpqm2$Data))
cal.station.cl4.gpqm2 <- subsetDimension(cal.station.cl4.gpqm2, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl5.pqm$Data))
cal.station.cl5.pqm <- subsetDimension(cal.station.cl5.pqm, dimension = "time", indices = idx)


wt_conditioned <- bindGrid(cal.station.cl1.pqm, cal.station.cl2.pqm, cal.station.cl3.pqm,
                           cal.station.cl4.gpqm2, cal.station.cl5.pqm, dimension = "time")

attr(wt_conditioned$Data, "dimensions") <- "time"
```
```{r}
#cambiar de tipo de biasCorrection y fillGridDates
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "eqm", cross.val = 'loo')
```


```{r}

# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))

index.combinated.rv20max <- MaxReturnValue(wt_conditioned)

index.combinated <- c(index.combinated, index.combinated.rv20max)

```

```{r}
index.eqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.eqm <- c(index.eqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.eqm.rv20max <- MaxReturnValue(cal.station.complete)

index.eqm<- c(index.eqm ,index.eqm.rv20max)

index.eqm
```
```{r}
diff.conditioned <- abs(index.obs-index.combinated)

diff.eqm <- abs(index.obs-index.eqm)
```


```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)

score.combinated <- c()
for (i in c(1:9)) {
  score.combinated <- c(score.combinated, norm.vector[[i]][5]) 
}
score.combinated <- mean(score.combinated)

scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
df <- data.frame(index.obs, index.combinated, index.eqm)

colnames(df) <- c("Observation","Conditioned", "EQM")

format(df, digits = 3, scientific = 5)
```
```{r}
bias.df <- data.frame(diff.conditioned, diff.eqm)

colnames(bias.df) <- c("Bias Conditioned", "Bias EQM")

format(bias.df, digits = 3, scientific = 5)
```

```{r}
df.st1 <- df
bias.df.st1 <- bias.df
```

```{r}
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100

names(bias.rel.cond) <- names(diff.conditioned)

bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100

names(bias.rel.no.cond) <- names(diff.conditioned)
```

```{r}
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)

colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias EQM")

format(bias.rel.df, digits = 3, scientific = 5)
```


```{r}
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))

abline(a = 0, b = 1)

station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))

points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))

idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))

station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)

points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)

legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))

grid() 
```

## Alofi, Niue
```{r}
i=2

station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
```


````{r}
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
index.obs <- c(index.obs, index.obs.rv20max)

index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
index.trmm <- c(index.trmm, index.trmm.rv20max)


```



### WT1

```{r}
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))


station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))


```

```{r}
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)

index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
```

```{r}
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")

station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")

cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "pqm",cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.pqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.eqm.cl1 <- index.cal.station.cl1


```

```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm2.cl1 <- index.cal.station.cl1


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i])) 
}

```

```{r}
normalization <- function(measure){
  measure.norm <- c()
  #measure must be a vector with the value of a certain measure of different calibrations
  for (i in c(1:length(measure))) {
    measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
  }
  return(measure.norm)
}
```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
```
```{r}
scores.st2.wt1 <- scores
```

### WT2
```{r}
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))


station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))

```

```{r}
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)

index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)

```

```{r}
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")

station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")

cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.pqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.eqm.cl2 <- index.cal.station.cl2


```

```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm2.cl2 <- index.cal.station.cl2


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st2.wt2 <- scores
```

### WT3

```{r}
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))


station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))

```

```{r}
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)

index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)

```

```{r}
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")

station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")

cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.pqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.eqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm2.cl3 <- index.cal.station.cl3


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)

score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st2.wt3 <- scores
```
### WT4

```{r}
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))


station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))

```

```{r}
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)

index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)


```

```{r}
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")

station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")


cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.pqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.eqm.cl4 <- index.cal.station.cl4


```

```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm2.cl4 <- index.cal.station.cl4


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)

score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st2.wt4 <- scores
```
### WT5

```{r}
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))


station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))

```

```{r}
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)

index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
```

```{r}
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")

station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")

cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.pqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.eqm.cl5 <- index.cal.station.cl5


```

```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm2.cl5 <- index.cal.station.cl5


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st2.wt5 <- scores
```




### Complete period (WO WTs)



```{r}
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)

index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
```
```{r}
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "pqm", cross.val = 'loo')

cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")

cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.pqm.complete <- index.cal.station.complete


```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "eqm", cross.val = 'loo')


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.eqm.complete <- index.cal.station.complete


```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", cross.val = "loo")


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm.complete <- index.cal.station.complete



```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", theta = .7)


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm2.complete <- index.cal.station.complete



```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.trmm.complete[i]-index.obs.complete[i]),abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
score.trmm <- c()
for (i in c(1:9)) {
  score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
}
score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][2]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][3]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][4]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][5]) 
}
score.gpqm2 <- mean(score.gpqm2)


scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.complete <- scores
```

```{r}
paste(names(scores.st2.wt1[1]),names(scores.st2.wt2[1]),names(scores.st2.wt3[1]),names(scores.st2.wt4[1]),names(scores.st2.wt5[1]), names(scores.complete[1]))
```

### Combination of techniques by WT

```{r}

cal.station.cl1.pqm <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "pqm", cross.val = "loo", wt = T)

cal.station.cl1.pqm$Dates$start <- as.POSIXct(cal.station.cl1.pqm$Dates$start,tz = "GMT")
cal.station.cl1.pqm$Dates$end <- as.POSIXct(cal.station.cl1.pqm$Dates$end,tz = "GMT")

cal.station.cl2.eqm <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "eqm", cross.val = "loo", wt = T)
cal.station.cl2.eqm$Dates$start <- as.POSIXct(cal.station.cl2.eqm$Dates$start,tz = "GMT")
cal.station.cl2.eqm$Dates$end <- as.POSIXct(cal.station.cl2.eqm$Dates$end,tz = "GMT")

cal.station.cl3.gpqm <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm", cross.val = "loo", wt = T)

cal.station.cl3.gpqm$Dates$start <- as.POSIXct(cal.station.cl3.gpqm$Dates$start,tz = "GMT")
cal.station.cl3.gpqm$Dates$end <- as.POSIXct(cal.station.cl3.gpqm$Dates$end,tz = "GMT")

cal.station.cl4.pqm <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "pqm", cross.val = "loo", wt = T)
cal.station.cl4.pqm$Dates$start <- as.POSIXct(cal.station.cl4.pqm$Dates$start,tz = "GMT")
cal.station.cl4.pqm$Dates$end <- as.POSIXct(cal.station.cl4.pqm$Dates$end,tz = "GMT")

cal.station.cl5.eqm <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "eqm", cross.val = "loo", wt = T)

cal.station.cl5.eqm$Dates$start <- as.POSIXct(cal.station.cl5.eqm$Dates$start,tz = "GMT")
cal.station.cl5.eqm$Dates$end <- as.POSIXct(cal.station.cl5.eqm$Dates$end,tz = "GMT")


idx <- which(!is.na(cal.station.cl1.pqm$Data))
cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl2.eqm$Data))
cal.station.cl2.eqm <- subsetDimension(cal.station.cl2.eqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl3.gpqm$Data))
cal.station.cl3.gpqm <- subsetDimension(cal.station.cl3.gpqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl4.pqm$Data))
cal.station.cl4.pqm <- subsetDimension(cal.station.cl4.pqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl5.eqm$Data))
cal.station.cl5.eqm <- subsetDimension(cal.station.cl5.eqm, dimension = "time", indices = idx)


wt_conditioned <- bindGrid(cal.station.cl1.pqm, cal.station.cl2.eqm, cal.station.cl3.gpqm,
                           cal.station.cl4.pqm, cal.station.cl5.eqm, dimension = "time")

attr(wt_conditioned$Data, "dimensions") <- "time"
```
```{r}
#cambiar de tipo de biasCorrection y fillGridDates
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "pqm", cross.val = 'loo')
```


```{r}

# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))

index.combinated.rv20max <- MaxReturnValue(wt_conditioned)

index.combinated <- c(index.combinated, index.combinated.rv20max)

```

```{r}
index.pqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.pqm <- c(index.pqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.pqm.rv20max <- MaxReturnValue(cal.station.complete)

index.pqm<- c(index.pqm ,index.pqm.rv20max)

index.pqm
```
```{r}
diff.conditioned <- abs(index.obs-index.combinated)

diff.pqm <- abs(index.obs-index.pqm)
```


```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)

score.combinated <- c()
for (i in c(1:9)) {
  score.combinated <- c(score.combinated, norm.vector[[i]][5]) 
}
score.combinated <- mean(score.combinated)

scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
df <- data.frame(index.obs, index.combinated, index.eqm)

colnames(df) <- c("Observation","Conditioned", "PQM")

format(df, digits = 3, scientific = 5)
```
```{r}
bias.df <- data.frame(diff.conditioned, diff.eqm)

colnames(bias.df) <- c("Bias Conditioned", "Bias PQM")

format(bias.df, digits = 3, scientific = 5)
```

```{r}
df.st1 <- df
bias.df.st1 <- bias.df
```

```{r}
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100

names(bias.rel.cond) <- names(diff.conditioned)

bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100

names(bias.rel.no.cond) <- names(diff.conditioned)
```

```{r}
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)

colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias PQM")

format(bias.rel.df, digits = 3, scientific = 5)
```


```{r}
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))

abline(a = 0, b = 1)

station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))

points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))

idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))

station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)

points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)

legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))

grid() 
```

## Rarotonga, Cook Islands

```{r}
i=3

station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
```


````{r}
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
index.obs <- c(index.obs, index.obs.rv20max)

index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
index.trmm <- c(index.trmm, index.trmm.rv20max)


```



### WT1

```{r}
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))


station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))


```

```{r}
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)

index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
```

```{r}
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")

station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")

cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "pqm",cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.pqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.eqm.cl1 <- index.cal.station.cl1


```

```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm2.cl1 <- index.cal.station.cl1


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i])) 
}

```

```{r}
normalization <- function(measure){
  measure.norm <- c()
  #measure must be a vector with the value of a certain measure of different calibrations
  for (i in c(1:length(measure))) {
    measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
  }
  return(measure.norm)
}
```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
```
```{r}
scores.st3.wt1 <- scores
```

### WT2
```{r}
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))


station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))

```

```{r}
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)

index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)

```

```{r}
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")

station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")

cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.pqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.eqm.cl2 <- index.cal.station.cl2


```

```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm2.cl2 <- index.cal.station.cl2


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st3.wt2 <- scores
```

### WT3

```{r}
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))


station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))

```

```{r}
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)

index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)

```

```{r}
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")

station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")

cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.pqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.eqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm2.cl3 <- index.cal.station.cl3


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st3.wt3 <- scores
```
### WT4

```{r}
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))


station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))

```

```{r}
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)

index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)


```

```{r}
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")

station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")


cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.pqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.eqm.cl4 <- index.cal.station.cl4


```

```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T) 


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm2.cl4 <- index.cal.station.cl4


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}

score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)

scores
```
```{r}
scores.st3.wt4 <- scores
```
### WT5

```{r}
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))


station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))

```

```{r}
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)

index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
```

```{r}
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")

station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")

cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.pqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.eqm.cl5 <- index.cal.station.cl5


```

```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm2.cl5 <- index.cal.station.cl5


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)


scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st3.wt5 <- scores
```




### Complete period (WO WTs)



```{r}
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)

index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
```
```{r}
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "pqm", cross.val = 'loo')

cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")

cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.pqm.complete <- index.cal.station.complete


```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "eqm", cross.val = 'loo')


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.eqm.complete <- index.cal.station.complete


```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", cross.val = "loo")


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm.complete <- index.cal.station.complete



```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", theta = .7, cross.val = "loo")


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm2.complete <- index.cal.station.complete



```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.trmm.complete[i]-index.obs.complete[i]),abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
score.trmm <- c()
for (i in c(1:9)) {
  score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
}
score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][2]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][3]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][4]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][5]) 
}
score.gpqm2 <- mean(score.gpqm2)


scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.complete <- scores
```

```{r}
paste(names(scores.st3.wt1[1]),names(scores.st3.wt2[1]),names(scores.st3.wt3[1]),names(scores.st3.wt4[1]),names(scores.st3.wt5[2]), names(scores.complete[1]))
```

### Combination of techniques by WT

```{r}
cal.station.cl1.pqm <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl1.pqm$Dates$start <- as.POSIXct(cal.station.cl1.pqm$Dates$start,tz = "GMT")
cal.station.cl1.pqm$Dates$end <- as.POSIXct(cal.station.cl1.pqm$Dates$end,tz = "GMT")

cal.station.cl2.gpqm2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm", theta = .7, cross.val = "loo", wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl2.gpqm2$Dates$start <- as.POSIXct(cal.station.cl2.gpqm2$Dates$start,tz = "GMT")
cal.station.cl2.gpqm2$Dates$end <- as.POSIXct(cal.station.cl2.gpqm2$Dates$end,tz = "GMT")

cal.station.cl3.gpqm2 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm", theta = .7, cross.val = "loo", wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl3.gpqm2$Dates$start <- as.POSIXct(cal.station.cl3.gpqm2$Dates$start,tz = "GMT")
cal.station.cl3.gpqm2$Dates$end <- as.POSIXct(cal.station.cl3.gpqm2$Dates$end,tz = "GMT")

cal.station.cl4.gpqm <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm", wt = T)


#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl4.gpqm$Dates$start <- as.POSIXct(cal.station.cl4.gpqm$Dates$start,tz = "GMT")
cal.station.cl4.gpqm$Dates$end <- as.POSIXct(cal.station.cl4.gpqm$Dates$end,tz = "GMT")

cal.station.cl5.gpqm2 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm", theta = .7, cross.val = 'loo', wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl5.gpqm2$Dates$start <- as.POSIXct(cal.station.cl5.gpqm2$Dates$start,tz = "GMT")
cal.station.cl5.gpqm2$Dates$end <- as.POSIXct(cal.station.cl5.gpqm2$Dates$end,tz = "GMT")



idx <- which(!is.na(cal.station.cl1.pqm$Data))
cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl2.gpqm2$Data))
cal.station.cl2.gpqm2 <- subsetDimension(cal.station.cl2.gpqm2, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl3.gpqm2$Data))
cal.station.cl3.gpqm2 <- subsetDimension(cal.station.cl3.gpqm2, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl4.gpqm$Data))
cal.station.cl4.gpqm <- subsetDimension(cal.station.cl4.gpqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl5.gpqm2$Data))
cal.station.cl5.gpqm2 <- subsetDimension(cal.station.cl5.gpqm2, dimension = "time", indices = idx)


wt_conditioned <- bindGrid(cal.station.cl1.pqm, cal.station.cl2.gpqm2, cal.station.cl3.gpqm2,
                           cal.station.cl4.gpqm, cal.station.cl5.gpqm2, dimension = "time")

attr(wt_conditioned$Data, "dimensions") <- "time"
```
```{r}
#cambiar de tipo de biasCorrection y fillGridDates
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "pqm", cross.val = "loo")

```


```{r}

# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))

index.combinated.rv20max <- MaxReturnValue(wt_conditioned)

index.combinated <- c(index.combinated, index.combinated.rv20max)

```

```{r}
index.pqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.pqm <- c(index.pqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.pqm.rv20max <- MaxReturnValue(cal.station.complete)

index.pqm<- c(index.pqm ,index.pqm.rv20max)

index.pqm
```
```{r}
diff.conditioned <- abs(index.obs-index.combinated)

diff.pqm <- abs(index.obs-index.pqm)
```


```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)

score.combinated <- c()
for (i in c(1:9)) {
  score.combinated <- c(score.combinated, norm.vector[[i]][5]) 
}
score.combinated <- mean(score.combinated)

scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
df <- data.frame(index.obs, index.combinated, index.pqm)

colnames(df) <- c("Observation","Conditioned", "GPQM")

format(df, digits = 3, scientific = 5)
```
```{r}
bias.df <- data.frame(diff.conditioned, diff.pqm)

colnames(bias.df) <- c("Bias Conditioned", "Bias PQM")

format(bias.df, digits = 3, scientific = 5)
```

```{r}
df.st1 <- df
bias.df.st1 <- bias.df
```

```{r}
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100

names(bias.rel.cond) <- names(diff.conditioned)

bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100

names(bias.rel.no.cond) <- names(diff.conditioned)
```

```{r}
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)

colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias GPQM")

format(bias.rel.df, digits = 3, scientific = 5)
```


```{r}
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))

abline(a = 0, b = 1)

station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))

points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))

idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))

station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)

points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)

legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))

grid() 
```
## Raoul Island, New Zealand
```{r}
i=4

station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
```


````{r}
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
index.obs <- c(index.obs, index.obs.rv20max)

index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
index.trmm <- c(index.trmm, index.trmm.rv20max)


```



### WT1

```{r}
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))


station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))


```

```{r}
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)

index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
```

```{r}
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")

station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")

cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "pqm",cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.pqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.eqm.cl1 <- index.cal.station.cl1


```

```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo' , wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm2.cl1 <- index.cal.station.cl1


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i])) 
}

```

```{r}
normalization <- function(measure){
  measure.norm <- c()
  #measure must be a vector with the value of a certain measure of different calibrations
  for (i in c(1:length(measure))) {
    measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
  }
  return(measure.norm)
}
```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
```
```{r}
scores.st4.wt1 <- scores
```

### WT2
```{r}
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))


station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))

```

```{r}
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)

index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)

```

```{r}
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")

station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")

cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.pqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.eqm.cl2 <- index.cal.station.cl2


```

```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm2.cl2 <- index.cal.station.cl2


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)

score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st4.wt2 <- scores
```

### WT3

```{r}
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))


station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))

```

```{r}
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)

index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)

```

```{r}
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")

station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")

cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.pqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.eqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm2.cl3 <- index.cal.station.cl3


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)

score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st4.wt3 <- scores
```
### WT4

```{r}
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))


station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))

```

```{r}
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)

index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)


```

```{r}
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")

station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")


cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.pqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.eqm.cl4 <- index.cal.station.cl4


```

```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm2.cl4 <- index.cal.station.cl4


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)

score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st4.wt4 <- scores
```
### WT5

```{r}
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))


station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))

```

```{r}
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)

index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
```

```{r}
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")

station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")

cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.pqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.eqm.cl5 <- index.cal.station.cl5


```

```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm2.cl5 <- index.cal.station.cl5


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)

score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st4.wt5 <- scores
```




### Complete period (WO WTs)



```{r}
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)

index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
```
```{r}
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "pqm", cross.val = 'loo')

cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")

cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.pqm.complete <- index.cal.station.complete


```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "eqm", cross.val = 'loo')


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.eqm.complete <- index.cal.station.complete


```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", cross.val = "loo")


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm.complete <- index.cal.station.complete



```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", theta = .7, cross.val = "loo")


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm2.complete <- index.cal.station.complete



```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.trmm.complete[i]-index.obs.complete[i]),abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
score.trmm <- c()
for (i in c(1:9)) {
  score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
}
score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][2]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][3]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][4]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][5]) 
}
score.gpqm2 <- mean(score.gpqm2)


scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.complete <- scores
```

```{r}
paste(names(scores.st4.wt1[1]),names(scores.st4.wt2[1]),names(scores.st4.wt3[1]),names(scores.st4.wt4[1]),names(scores.st4.wt5[1]), names(scores.complete[1]))
```

### Combination of techniques by WT

```{r}
cal.station.cl1.eqm <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "eqm", cross.val = "loo", wt = T)


#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl1.eqm$Dates$start <- as.POSIXct(cal.station.cl1.eqm$Dates$start,tz = "GMT")
cal.station.cl1.eqm$Dates$end <- as.POSIXct(cal.station.cl1.eqm$Dates$end,tz = "GMT")

cal.station.cl2.eqm <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "eqm", cross.val = "loo", wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))


cal.station.cl2.eqm$Dates$start <- as.POSIXct(cal.station.cl2.eqm$Dates$start,tz = "GMT")
cal.station.cl2.eqm$Dates$end <- as.POSIXct(cal.station.cl2.eqm$Dates$end,tz = "GMT")

cal.station.cl3.pqm <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "pqm", cross.val = "loo", wt = T) 

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl3.pqm$Dates$start <- as.POSIXct(cal.station.cl3.pqm$Dates$start,tz = "GMT")
cal.station.cl3.pqm$Dates$end <- as.POSIXct(cal.station.cl3.pqm$Dates$end,tz = "GMT")

cal.station.cl4.eqm <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "eqm", cross.val = "loo", wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl4.eqm$Dates$start <- as.POSIXct(cal.station.cl4.eqm$Dates$start,tz = "GMT")
cal.station.cl4.eqm$Dates$end <- as.POSIXct(cal.station.cl4.eqm$Dates$end,tz = "GMT")

cal.station.cl5.eqm <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "eqm", cross.val = "loo", wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl5.eqm$Dates$start <- as.POSIXct(cal.station.cl5.eqm$Dates$start,tz = "GMT")
cal.station.cl5.eqm$Dates$end <- as.POSIXct(cal.station.cl5.eqm$Dates$end,tz = "GMT")


idx <- which(!is.na(cal.station.cl1.eqm$Data))
cal.station.cl1.eqm <- subsetDimension(cal.station.cl1.eqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl2.eqm$Data))
cal.station.cl2.eqm <- subsetDimension(cal.station.cl2.eqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl3.pqm$Data))
cal.station.cl3.pqm <- subsetDimension(cal.station.cl3.pqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl4.eqm$Data))
cal.station.cl4.eqm <- subsetDimension(cal.station.cl4.eqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl5.eqm$Data))
cal.station.cl5.eqm <- subsetDimension(cal.station.cl5.eqm, dimension = "time", indices = idx)


wt_conditioned <- bindGrid(cal.station.cl1.eqm, cal.station.cl2.eqm, cal.station.cl3.pqm,
                           cal.station.cl4.eqm, cal.station.cl5.eqm, dimension = "time")

attr(wt_conditioned$Data, "dimensions") <- "time"
```
```{r}
#cambiar de tipo de biasCorrection y fillGridDates
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "eqm", cross.val = 'loo')
```


```{r}

# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))

index.combinated.rv20max <- MaxReturnValue(wt_conditioned)

index.combinated <- c(index.combinated, index.combinated.rv20max)

```

```{r}
index.eqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.eqm <- c(index.eqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.eqm.rv20max <- MaxReturnValue(cal.station.complete)

index.eqm<- c(index.eqm ,index.eqm.rv20max)

index.eqm
```
```{r}
diff.conditioned <- abs(index.obs-index.combinated)

diff.eqm <- abs(index.obs-index.eqm)
```


```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)

score.combinated <- c()
for (i in c(1:9)) {
  score.combinated <- c(score.combinated, norm.vector[[i]][5]) 
}
score.combinated <- mean(score.combinated)

scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
df <- data.frame(index.obs, index.combinated, index.eqm)

colnames(df) <- c("Observation","Conditioned", "EQM")

format(df, digits = 3, scientific = 5)
```
```{r}
bias.df <- data.frame(diff.conditioned, diff.eqm)

colnames(bias.df) <- c("Bias Conditioned", "Bias EQM")

format(bias.df, digits = 3, scientific = 5)
```

```{r}
df.st1 <- df
bias.df.st1 <- bias.df
```

```{r}
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100

names(bias.rel.cond) <- names(diff.conditioned)

bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100

names(bias.rel.no.cond) <- names(diff.conditioned)
```

```{r}
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)

colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias EQM")

format(bias.rel.df, digits = 3, scientific = 5)
```


```{r}
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))

abline(a = 0, b = 1)

station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))

points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))

idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))

station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)

points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)

legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))

grid() 
```
## ocean buoy?
```{r}
i=5

station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
```


````{r}
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
index.obs <- c(index.obs, index.obs.rv20max)

index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
index.trmm <- c(index.trmm, index.trmm.rv20max)


```



### WT1

```{r}
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))


station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))


```

```{r}
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)

index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
```

```{r}
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")

station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")

cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "pqm",cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.pqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.eqm.cl1 <- index.cal.station.cl1


```

```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm2.cl1 <- index.cal.station.cl1


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i])) 
}

```

```{r}
normalization <- function(measure){
  measure.norm <- c()
  #measure must be a vector with the value of a certain measure of different calibrations
  for (i in c(1:length(measure))) {
    measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
  }
  return(measure.norm)
}
```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
```
```{r}
scores.st5.wt1 <- scores
```

### WT2
```{r}
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))


station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))

```

```{r}
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)

index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)

```

```{r}
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")

station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")

cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "pqm", cross.val = 'loo')


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.pqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T) 


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.eqm.cl2 <- index.cal.station.cl2


```

```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm2.cl2 <- index.cal.station.cl2


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st5.wt2 <- scores
```

### WT3

```{r}
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))


station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))

```

```{r}
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)

index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)

```

```{r}
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")

station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")

cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.pqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.eqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm2.cl3 <- index.cal.station.cl3


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st5.wt3 <- scores
```
### WT4

```{r}
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))


station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))

```

```{r}
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)

index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)


```

```{r}
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")

station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")


cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.pqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.eqm.cl4 <- index.cal.station.cl4


```

```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm2.cl4 <- index.cal.station.cl4


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st5.wt4 <- scores
```
### WT5

```{r}
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))


station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))

```

```{r}
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)

index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
```

```{r}
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")

station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")

cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.pqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.eqm.cl5 <- index.cal.station.cl5


```

```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm2.cl5 <- index.cal.station.cl5


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st5.wt5 <- scores
```




### Complete period (WO WTs)



```{r}
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)

index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
```
```{r}
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "pqm", cross.val = 'loo')

cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")

cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.pqm.complete <- index.cal.station.complete


```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "eqm", cross.val = 'loo')


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.eqm.complete <- index.cal.station.complete


```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", cross.val = "loo")


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm.complete <- index.cal.station.complete



```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", theta = .7, cross.val = "loo")


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm2.complete <- index.cal.station.complete



```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.trmm.complete[i]-index.obs.complete[i]),abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
score.trmm <- c()
for (i in c(1:9)) {
  score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
}
score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][2]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][3]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][4]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][5]) 
}
score.gpqm2 <- mean(score.gpqm2)


scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.complete <- scores
```

```{r}
paste(names(scores.st5.wt1[1]),names(scores.st5.wt2[1]),names(scores.st5.wt3[1]),names(scores.st5.wt4[1]),names(scores.st5.wt5[1]), names(scores.complete[1]))
```

### Combination of techniques by WT

```{r}
cal.station.cl1.eqm <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "eqm", cross.val = "loo", wt = T)


#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl1.eqm$Dates$start <- as.POSIXct(cal.station.cl1.eqm$Dates$start,tz = "GMT")
cal.station.cl1.eqm$Dates$end <- as.POSIXct(cal.station.cl1.eqm$Dates$end,tz = "GMT")

cal.station.cl2.eqm <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "eqm", cross.val = "loo", wt = T)


#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl2.eqm$Dates$start <- as.POSIXct(cal.station.cl2.eqm$Dates$start,tz = "GMT")
cal.station.cl2.eqm$Dates$end <- as.POSIXct(cal.station.cl2.eqm$Dates$end,tz = "GMT")

cal.station.cl3.gpqm2 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm", theta = .7, cross.val = 'loo', wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl3.gpqm2$Dates$start <- as.POSIXct(cal.station.cl3.gpqm2$Dates$start,tz = "GMT")
cal.station.cl3.gpqm2$Dates$end <- as.POSIXct(cal.station.cl3.gpqm2$Dates$end,tz = "GMT")

cal.station.cl4.pqm <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "pqm", cross.val = "loo", wt = T)


#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl4.pqm$Dates$start <- as.POSIXct(cal.station.cl4.pqm$Dates$start,tz = "GMT")
cal.station.cl4.pqm$Dates$end <- as.POSIXct(cal.station.cl4.pqm$Dates$end,tz = "GMT")

cal.station.cl5.gpqm2 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm",theta = .7, cross.val = 'loo', wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl5.gpqm2$Dates$start <- as.POSIXct(cal.station.cl5.gpqm2$Dates$start,tz = "GMT")
cal.station.cl5.gpqm2$Dates$end <- as.POSIXct(cal.station.cl5.gpqm2$Dates$end,tz = "GMT")

idx <- which(!is.na(cal.station.cl1.eqm$Data))
cal.station.cl1.eqm <- subsetDimension(cal.station.cl1.eqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl2.eqm$Data))
cal.station.cl2.eqm <- subsetDimension(cal.station.cl2.eqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl3.gpqm2$Data))
cal.station.cl3.gpqm2 <- subsetDimension(cal.station.cl3.gpqm2, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl4.pqm$Data))
cal.station.cl4.pqm <- subsetDimension(cal.station.cl4.pqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl5.gpqm2$Data))
cal.station.cl5.gpqm2 <- subsetDimension(cal.station.cl5.gpqm2, dimension = "time", indices = idx)


wt_conditioned <- bindGrid(cal.station.cl1.eqm, cal.station.cl2.eqm, cal.station.cl3.gpqm2,
                           cal.station.cl4.pqm, cal.station.cl5.gpqm2, dimension = "time")

attr(wt_conditioned$Data, "dimensions") <- "time"
```
```{r}
#cambiar de tipo de biasCorrection y fillGridDates
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "eqm", cross.val = 'loo')
```


```{r}

# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))

index.combinated.rv20max <- MaxReturnValue(wt_conditioned)

index.combinated <- c(index.combinated, index.combinated.rv20max)

```

```{r}
index.eqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.eqm <- c(index.eqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.eqm.rv20max <- MaxReturnValue(cal.station.complete)

index.eqm<- c(index.eqm ,index.eqm.rv20max)

index.eqm
```
```{r}
diff.conditioned <- abs(index.obs-index.combinated)

diff.eqm <- abs(index.obs-index.eqm)
```


```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)

score.combinated <- c()
for (i in c(1:9)) {
  score.combinated <- c(score.combinated, norm.vector[[i]][5]) 
}
score.combinated <- mean(score.combinated)

scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
df <- data.frame(index.obs, index.combinated, index.eqm)

colnames(df) <- c("Observation","Conditioned", "EQM")

format(df, digits = 3, scientific = 5)
```
```{r}
bias.df <- data.frame(diff.conditioned, diff.eqm)

colnames(bias.df) <- c("Bias Conditioned", "Bias EQM")

format(bias.df, digits = 3, scientific = 5)
```

```{r}
df.st1 <- df
bias.df.st1 <- bias.df
```

```{r}
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100

names(bias.rel.cond) <- names(diff.conditioned)

bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100

names(bias.rel.no.cond) <- names(diff.conditioned)
```

```{r}
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)

colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias EQM")

format(bias.rel.df, digits = 3, scientific = 5)
```


```{r}
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))

abline(a = 0, b = 1)

station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))

points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))

idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))

station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)

points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)

legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))

grid() 
```
## Aoloau, American  Samoa
```{r}
i=6

station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
```


````{r}
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
index.obs <- c(index.obs, index.obs.rv20max)

index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
index.trmm <- c(index.trmm, index.trmm.rv20max)


```



### WT1

```{r}
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))


station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))


```

```{r}
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)

index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
```

```{r}
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")

station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")

cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "pqm",cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.pqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.eqm.cl1 <- index.cal.station.cl1


```

```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm2.cl1 <- index.cal.station.cl1


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i])) 
}

```

```{r}
normalization <- function(measure){
  measure.norm <- c()
  #measure must be a vector with the value of a certain measure of different calibrations
  for (i in c(1:length(measure))) {
    measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
  }
  return(measure.norm)
}
```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
```
```{r}
scores.st6.wt1 <- scores
```

### WT2
```{r}
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))


station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))

```

```{r}
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)

index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)

```

```{r}
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")

station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")

cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.pqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.eqm.cl2 <- index.cal.station.cl2


```

```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm2.cl2 <- index.cal.station.cl2


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st6.wt2 <- scores
```

### WT3

```{r}
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))


station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))

```

```{r}
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)

index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)

```

```{r}
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")

station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")

cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.pqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.eqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm2.cl3 <- index.cal.station.cl3


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st6.wt3 <- scores
```
### WT4

```{r}
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))


station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))

```

```{r}
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)

index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)


```

```{r}
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")

station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")


cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.pqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.eqm.cl4 <- index.cal.station.cl4


```

```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm2.cl4 <- index.cal.station.cl4


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st6.wt4 <- scores
```
### WT5

```{r}
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))


station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))

```

```{r}
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)

index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
```

```{r}
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")

station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")

cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.pqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.eqm.cl5 <- index.cal.station.cl5


```

```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm2.cl5 <- index.cal.station.cl5


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st6.wt5 <- scores
```




### Complete period (WO WTs)



```{r}
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)

index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
```
```{r}
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "pqm", cross.val = 'loo')

cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")

cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.pqm.complete <- index.cal.station.complete


```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "eqm", cross.val = 'loo')


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.eqm.complete <- index.cal.station.complete


```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", cross.val = "loo")


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm.complete <- index.cal.station.complete



```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", theta = .7, cross.val = "loo")


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm2.complete <- index.cal.station.complete



```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.trmm.complete[i]-index.obs.complete[i]),abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
score.trmm <- c()
for (i in c(1:9)) {
  score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
}
score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][2]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][3]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][4]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][5]) 
}
score.gpqm2 <- mean(score.gpqm2)


scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.complete <- scores
```

```{r}
paste(names(scores.st6.wt1[1]),names(scores.st6.wt2[1]),names(scores.st6.wt3[1]),names(scores.st6.wt4[1]),names(scores.st6.wt5[1]), names(scores.complete[1]))

```

### Combination of techniques by WT

```{r}
cal.station.cl1.eqm <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "eqm",cross.val = "loo", wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))
cal.station.cl1.eqm$Dates$start <- as.POSIXct(cal.station.cl1.eqm$Dates$start,tz = "GMT")
cal.station.cl1.eqm$Dates$end <- as.POSIXct(cal.station.cl1.eqm$Dates$end,tz = "GMT")

cal.station.cl2.pqm <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "pqm", cross.val = "loo", wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl2.pqm$Dates$start <- as.POSIXct(cal.station.cl2.pqm$Dates$start,tz = "GMT")
cal.station.cl2.pqm$Dates$end <- as.POSIXct(cal.station.cl2.pqm$Dates$end,tz = "GMT")

cal.station.cl3.pqm <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "pqm", cross.val = "loo", wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl3.pqm$Dates$start <- as.POSIXct(cal.station.cl3.pqm$Dates$start,tz = "GMT")
cal.station.cl3.pqm$Dates$end <- as.POSIXct(cal.station.cl3.pqm$Dates$end,tz = "GMT")

cal.station.cl4.eqm <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "eqm", cross.val = "loo", wt = T)


#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl4.eqm$Dates$start <- as.POSIXct(cal.station.cl4.eqm$Dates$start,tz = "GMT")
cal.station.cl4.eqm$Dates$end <- as.POSIXct(cal.station.cl4.eqm$Dates$end,tz = "GMT")

cal.station.cl5.eqm <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl5.eqm$Dates$start <- as.POSIXct(cal.station.cl5.eqm$Dates$start,tz = "GMT")
cal.station.cl5.eqm$Dates$end <- as.POSIXct(cal.station.cl5.eqm$Dates$end,tz = "GMT")



idx <- which(!is.na(cal.station.cl1.eqm$Data))
cal.station.cl1.eqm <- subsetDimension(cal.station.cl1.eqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl2.pqm$Data))
cal.station.cl2.pqm <- subsetDimension(cal.station.cl2.pqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl3.pqm$Data))
cal.station.cl3.pqm <- subsetDimension(cal.station.cl3.pqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl4.eqm$Data))
cal.station.cl4.eqm <- subsetDimension(cal.station.cl4.eqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl5.eqm$Data))
cal.station.cl5.eqm <- subsetDimension(cal.station.cl5.eqm, dimension = "time", indices = idx)


wt_conditioned <- bindGrid(cal.station.cl1.eqm, cal.station.cl2.pqm, cal.station.cl3.pqm,
                           cal.station.cl4.eqm, cal.station.cl5.eqm, dimension = "time")

attr(wt_conditioned$Data, "dimensions") <- "time"
```
```{r}
#cambiar de tipo de biasCorrection y fillGridDates
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "pqm", cross.val = 'loo')
```


```{r}

# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))

index.combinated.rv20max <- MaxReturnValue(wt_conditioned)

index.combinated <- c(index.combinated, index.combinated.rv20max)

```

```{r}
index.pqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.pqm <- c(index.pqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.pqm.rv20max <- MaxReturnValue(cal.station.complete)

index.pqm<- c(index.pqm ,index.pqm.rv20max)

index.pqm
```
```{r}
diff.conditioned <- abs(index.obs-index.combinated)

diff.pqm <- abs(index.obs-index.pqm)
```


```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)

score.combinated <- c()
for (i in c(1:9)) {
  score.combinated <- c(score.combinated, norm.vector[[i]][5]) 
}
score.combinated <- mean(score.combinated)

scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
df <- data.frame(index.obs, index.combinated, index.cal.station.pqm.complete)

colnames(df) <- c("Observation","Conditioned", "PQM")

format(df, digits = 3, scientific = 5)
```
```{r}
bias.df <- data.frame(diff.conditioned, diff.pqm)

colnames(bias.df) <- c("Bias Conditioned", "Bias PQM")

format(bias.df, digits = 3, scientific = 5)
```

```{r}
df.st1 <- df
bias.df.st1 <- bias.df
```

```{r}
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100

names(bias.rel.cond) <- names(diff.conditioned)

bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100

names(bias.rel.no.cond) <- names(diff.conditioned)
```

```{r}
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)

colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias PQM")

format(bias.rel.df, digits = 3, scientific = 5)
```


```{r}
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))

abline(a = 0, b = 1)

station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))

points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))

idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))

station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)

points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)

legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))

grid() 
```
## Nu'uuli, American Samoa
```{r}
i=7

station.trmm <- subsetGrid(precip_trmm, station.id = precip_trmm$Metadata$station_id[i])
station.obs <- subsetGrid(precip_obs, station.id = precip_trmm$Metadata$station_id[i])
```


````{r}
index.obs <- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs <- c(index.obs, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.rv20max <- MaxReturnValue(station.obs)
index.obs <- c(index.obs, index.obs.rv20max)

index.trmm <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.rv20max <- MaxReturnValue(station.trmm)
index.trmm <- c(index.trmm, index.trmm.rv20max)


```



### WT1

```{r}
station.obs.cl1 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 1))


station.trmm.cl1 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 1))


```

```{r}
index.obs.cl1 <- valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl1 <- c(index.obs.cl1, valueIndex1D(station.obs.cl1$Data[!is.na(station.obs.cl1$Data)], index.codes = "P98WetAmount"))
index.obs.cl1.rv20max <- MaxReturnValue(station.obs.cl1)
index.obs.cl1 <- c(index.obs.cl1, index.obs.cl1.rv20max)

index.trmm.cl1 <- valueIndex1D(station.trmm.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl1.rv20max <- MaxReturnValue(station.trmm.cl1)
index.trmm.cl1 <- c(index.trmm.cl1, index.trmm.cl1.rv20max)
```

```{r}
station.obs.cl1 <- setTimeResolution(station.obs.cl1, time_resolution = "DD")
station.trmm.cl1 <- setTimeResolution(station.trmm.cl1, time_resolution = "DD")

station.obs.cl1 <- setGridDates.asPOSIXlt(station.obs.cl1, tz = "UTC")
station.trmm.cl1 <- setGridDates.asPOSIXlt(station.trmm.cl1, tz = "UTC")

cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "pqm",cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.pqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.eqm.cl1 <- index.cal.station.cl1


```

```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm.cl1 <- index.cal.station.cl1


```


```{r}
cal.station.cl1 <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl1 <- subsetDimension(cal.station.cl1, dimension = "time", indices = which(!is.na(cal.station.cl1$Data)))

cal.station.cl1$Dates$start <- as.POSIXct(cal.station.cl1$Dates$start,tz = "GMT")
cal.station.cl1$Dates$end <- as.POSIXct(cal.station.cl1$Dates$end,tz = "GMT")

index.cal.station.cl1 <- valueIndex1D(cal.station.cl1$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl1 <- c(index.cal.station.cl1, valueIndex1D(cal.station.cl1$Data[!is.na(cal.station.cl1$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl1.rv20max <- MaxReturnValue(cal.station.cl1)

index.cal.station.cl1 <- c(index.cal.station.cl1, index.cal.station.cl1.rv20max)

index.cal.station.gpqm2.cl1 <- index.cal.station.cl1


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.eqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm.cl1[i]-index.obs.cl1[i]), abs(index.cal.station.gpqm2.cl1[i]-index.obs.cl1[i])) 
}

```

```{r}
normalization <- function(measure){
  measure.norm <- c()
  #measure must be a vector with the value of a certain measure of different calibrations
  for (i in c(1:length(measure))) {
    measure.norm <- c(measure.norm, 1-((measure[i]-min(measure))/(max(measure)-min(measure))))
  }
  return(measure.norm)
}
```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT1","EQM-WT1","GPQM-WT1","GPQM2-WT1")
scores <- sort(scores, decreasing = T)
```
```{r}
scores.st7.wt1 <- scores
```

### WT2
```{r}
station.obs.cl2 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 2))


station.trmm.cl2 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 2))

```

```{r}
index.obs.cl2 <- valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl2 <- c(index.obs.cl2, valueIndex1D(station.obs.cl2$Data[!is.na(station.obs.cl2$Data)], index.codes = "P98WetAmount"))
index.obs.cl2.rv20max <- MaxReturnValue(station.obs.cl2)
index.obs.cl2 <- c(index.obs.cl2, index.obs.cl2.rv20max)

index.trmm.cl2 <- valueIndex1D(station.trmm.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl2.rv20max <- MaxReturnValue(station.trmm.cl2)
index.trmm.cl2 <- c(index.trmm.cl2, index.trmm.cl2.rv20max)

```

```{r}
station.obs.cl2 <- setTimeResolution(station.obs.cl2, time_resolution = "DD")
station.trmm.cl2 <- setTimeResolution(station.trmm.cl2, time_resolution = "DD")

station.obs.cl2 <- setGridDates.asPOSIXlt(station.obs.cl2, tz = "UTC")
station.trmm.cl2 <- setGridDates.asPOSIXlt(station.trmm.cl2, tz = "UTC")

cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.pqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.eqm.cl2 <- index.cal.station.cl2


```

```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm.cl2 <- index.cal.station.cl2


```


```{r}
cal.station.cl2 <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl2 <- subsetDimension(cal.station.cl2, dimension = "time", indices = which(!is.na(cal.station.cl2$Data)))

cal.station.cl2$Dates$start <- as.POSIXct(cal.station.cl2$Dates$start,tz = "GMT")
cal.station.cl2$Dates$end <- as.POSIXct(cal.station.cl2$Dates$end,tz = "GMT")

index.cal.station.cl2 <- valueIndex1D(cal.station.cl2$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl2 <- c(index.cal.station.cl2, valueIndex1D(cal.station.cl2$Data[!is.na(cal.station.cl2$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl2.rv20max <- MaxReturnValue(cal.station.cl2)

index.cal.station.cl2 <- c(index.cal.station.cl2, index.cal.station.cl2.rv20max)

index.cal.station.gpqm2.cl2 <- index.cal.station.cl2


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.eqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm.cl2[i]-index.obs.cl2[i]), abs(index.cal.station.gpqm2.cl2[i]-index.obs.cl2[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT2","EQM-WT2","GPQM-WT2","GPQM2-WT2")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st7.wt2 <- scores
```

### WT3

```{r}
station.obs.cl3 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 3))


station.trmm.cl3 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 3))

```

```{r}
index.obs.cl3 <- valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl3 <- c(index.obs.cl3, valueIndex1D(station.obs.cl3$Data[!is.na(station.obs.cl3$Data)], index.codes = "P98WetAmount"))
index.obs.cl3.rv20max <- MaxReturnValue(station.obs.cl3)
index.obs.cl3 <- c(index.obs.cl3, index.obs.cl3.rv20max)

index.trmm.cl3 <- valueIndex1D(station.trmm.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl3.rv20max <- MaxReturnValue(station.trmm.cl3)
index.trmm.cl3 <- c(index.trmm.cl3, index.trmm.cl3.rv20max)

```

```{r}
station.obs.cl3 <- setTimeResolution(station.obs.cl3, time_resolution = "DD")
station.trmm.cl3 <- setTimeResolution(station.trmm.cl3, time_resolution = "DD")

station.obs.cl3 <- setGridDates.asPOSIXlt(station.obs.cl3, tz = "UTC")
station.trmm.cl3 <- setGridDates.asPOSIXlt(station.trmm.cl3, tz = "UTC")

cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.pqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.eqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm.cl3 <- index.cal.station.cl3


```


```{r}
cal.station.cl3 <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl3 <- subsetDimension(cal.station.cl3, dimension = "time", indices = which(!is.na(cal.station.cl3$Data)))

cal.station.cl3$Dates$start <- as.POSIXct(cal.station.cl3$Dates$start,tz = "GMT")
cal.station.cl3$Dates$end <- as.POSIXct(cal.station.cl3$Dates$end,tz = "GMT")

index.cal.station.cl3 <- valueIndex1D(cal.station.cl3$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl3 <- c(index.cal.station.cl3, valueIndex1D(cal.station.cl3$Data[!is.na(cal.station.cl3$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl3.rv20max <- MaxReturnValue(cal.station.cl3)

index.cal.station.cl3 <- c(index.cal.station.cl3, index.cal.station.cl3.rv20max)

index.cal.station.gpqm2.cl3 <- index.cal.station.cl3


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.eqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm.cl3[i]-index.obs.cl3[i]), abs(index.cal.station.gpqm2.cl3[i]-index.obs.cl3[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT3","EQM-WT3","GPQM-WT3","GPQM2-WT3")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st7.wt3 <- scores
```
### WT4

```{r}
station.obs.cl4 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 4))


station.trmm.cl4 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 4))

```

```{r}
index.obs.cl4 <- valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl4 <- c(index.obs.cl4, valueIndex1D(station.obs.cl4$Data[!is.na(station.obs.cl4$Data)], index.codes = "P98WetAmount"))
index.obs.cl4.rv20max <- MaxReturnValue(station.obs.cl4)
index.obs.cl4 <- c(index.obs.cl4, index.obs.cl4.rv20max)

index.trmm.cl4 <- valueIndex1D(station.trmm.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl4.rv20max <- MaxReturnValue(station.trmm.cl4)
index.trmm.cl4 <- c(index.trmm.cl4, index.trmm.cl4.rv20max)


```

```{r}
station.obs.cl4 <- setTimeResolution(station.obs.cl4, time_resolution = "DD")
station.trmm.cl4 <- setTimeResolution(station.trmm.cl4, time_resolution = "DD")

station.obs.cl4 <- setGridDates.asPOSIXlt(station.obs.cl4, tz = "UTC")
station.trmm.cl4 <- setGridDates.asPOSIXlt(station.trmm.cl4, tz = "UTC")


cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.pqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.eqm.cl4 <- index.cal.station.cl4


```

```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm.cl4 <- index.cal.station.cl4


```


```{r}
cal.station.cl4 <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl4 <- subsetDimension(cal.station.cl4, dimension = "time", indices = which(!is.na(cal.station.cl4$Data)))

cal.station.cl4$Dates$start <- as.POSIXct(cal.station.cl4$Dates$start,tz = "GMT")
cal.station.cl4$Dates$end <- as.POSIXct(cal.station.cl4$Dates$end,tz = "GMT")

index.cal.station.cl4 <- valueIndex1D(cal.station.cl4$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl4 <- c(index.cal.station.cl4, valueIndex1D(cal.station.cl4$Data[!is.na(cal.station.cl4$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl4.rv20max <- MaxReturnValue(cal.station.cl4)

index.cal.station.cl4 <- c(index.cal.station.cl4, index.cal.station.cl4.rv20max)

index.cal.station.gpqm2.cl4 <- index.cal.station.cl4


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.eqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm.cl4[i]-index.obs.cl4[i]), abs(index.cal.station.gpqm2.cl4[i]-index.obs.cl4[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT4","EQM-WT4","GPQM-WT4","GPQM2-WT4")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st7.wt4 <- scores
```
### WT5

```{r}
station.obs.cl5 <- subsetDimension(station.obs, dimension = "time", indices = which(kmModel5$cluster == 5))


station.trmm.cl5 <- subsetDimension(station.trmm, dimension = "time", indices = which(kmModel5$cluster == 5))

```

```{r}
index.obs.cl5 <- valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.cl5 <- c(index.obs.cl5, valueIndex1D(station.obs.cl5$Data[!is.na(station.obs.cl5$Data)], index.codes = "P98WetAmount"))
index.obs.cl5.rv20max <- MaxReturnValue(station.obs.cl5)
index.obs.cl5 <- c(index.obs.cl5, index.obs.cl5.rv20max)

index.trmm.cl5 <- valueIndex1D(station.trmm.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.cl5.rv20max <- MaxReturnValue(station.trmm.cl5)
index.trmm.cl5 <- c(index.trmm.cl5, index.trmm.cl5.rv20max)
```

```{r}
station.obs.cl5 <- setTimeResolution(station.obs.cl5, time_resolution = "DD")
station.trmm.cl5 <- setTimeResolution(station.trmm.cl5, time_resolution = "DD")

station.obs.cl5 <- setGridDates.asPOSIXlt(station.obs.cl5, tz = "UTC")
station.trmm.cl5 <- setGridDates.asPOSIXlt(station.trmm.cl5, tz = "UTC")

cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.pqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.eqm.cl5 <- index.cal.station.cl5


```

```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm", cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm.cl5 <- index.cal.station.cl5


```


```{r}
cal.station.cl5 <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "gpqm" , theta = .7, cross.val = 'loo', wt = T)


cal.station.cl5 <- subsetDimension(cal.station.cl5, dimension = "time", indices = which(!is.na(cal.station.cl5$Data)))

cal.station.cl5$Dates$start <- as.POSIXct(cal.station.cl5$Dates$start,tz = "GMT")
cal.station.cl5$Dates$end <- as.POSIXct(cal.station.cl5$Dates$end,tz = "GMT")

index.cal.station.cl5 <- valueIndex1D(cal.station.cl5$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.cl5 <- c(index.cal.station.cl5, valueIndex1D(cal.station.cl5$Data[!is.na(cal.station.cl5$Data)], index.codes = "P98WetAmount"))

index.cal.station.cl5.rv20max <- MaxReturnValue(cal.station.cl5)

index.cal.station.cl5 <- c(index.cal.station.cl5, index.cal.station.cl5.rv20max)

index.cal.station.gpqm2.cl5 <- index.cal.station.cl5


```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.eqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm.cl5[i]-index.obs.cl5[i]), abs(index.cal.station.gpqm2.cl5[i]-index.obs.cl5[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)


score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)




scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("PQM-WT5","EQM-WT5","GPQM-WT5","GPQM2-WT5")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.st7.wt5 <- scores
```




### Complete period (WO WTs)



```{r}
index.obs.complete<- valueIndex1D(station.obs$Data[!is.na(station.obs$Data)],index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))
index.obs.complete<- c(index.obs.complete, valueIndex1D(station.obs$Data[!is.na(station.obs$Data)], index.codes = "P98WetAmount"))
index.obs.complete.rv20max <- MaxReturnValue(station.obs)
index.obs.complete <- c(index.obs.complete, index.obs.complete.rv20max)

index.trmm.complete <- valueIndex1D(station.trmm$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet","P98WetAmount"))
index.trmm.complete.rv20max <- MaxReturnValue(station.trmm)
index.trmm.complete <- c(index.trmm.complete, index.trmm.complete.rv20max)
```
```{r}
station.obs <- setGridDates.asPOSIXlt(station.obs, tz = "UTC")
station.trmm <- setGridDates.asPOSIXlt(station.trmm, tz = "UTC")
```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "pqm", cross.val = 'loo')

cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")
cal.station.complete <- setTimeResolution(cal.station.complete, time_resolution = "DD")

cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.pqm.complete <- index.cal.station.complete


```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "eqm", cross.val = 'loo')


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.eqm.complete <- index.cal.station.complete


```

```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", cross.val = 'loo')


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm.complete <- index.cal.station.complete



```


```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "gpqm", theta = .7, cross.val = 'loo')


cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(cal.station.complete$Data)))

cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.cal.station.complete <- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.cal.station.complete <- c(index.cal.station.complete, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.cal.station.complete.rv20max <- MaxReturnValue(cal.station.complete)

index.cal.station.complete <- c(index.cal.station.complete, index.cal.station.complete.rv20max)

index.cal.station.gpqm2.complete <- index.cal.station.complete



```



```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)


scores <- c(score.trmm,score.pqm, score.eqm, score.gpqm, score.gpqm2)
names(scores) <- c("TRMM","PQM-C","EQM-C","GPQM-C","GPQM2-C")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
scores.complete <- scores
```

```{r}
paste(names(scores.st7.wt1[1]),names(scores.st7.wt2[1]),names(scores.st7.wt3[1]),names(scores.st7.wt4[1]),names(scores.st7.wt5[1]), names(scores.complete[1]))
```

### Combination of techniques by WT

```{r}
cal.station.cl1.pqm <- biasCorrection(y = station.obs.cl1, x = station.trmm.cl1, precipitation = TRUE,  method = "pqm", cross.val = 'loo', wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl1.pqm$Dates$start <- as.POSIXct(cal.station.cl1.pqm$Dates$start,tz = "GMT")
cal.station.cl1.pqm$Dates$end <- as.POSIXct(cal.station.cl1.pqm$Dates$end,tz = "GMT")

cal.station.cl2.eqm <- biasCorrection(y = station.obs.cl2, x = station.trmm.cl2, precipitation = TRUE,  method = "eqm", cross.val = 'loo', wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl2.eqm$Dates$start <- as.POSIXct(cal.station.cl2.eqm$Dates$start,tz = "GMT")
cal.station.cl2.eqm$Dates$end <- as.POSIXct(cal.station.cl2.eqm$Dates$end,tz = "GMT")

cal.station.cl3.pqm <- biasCorrection(y = station.obs.cl3, x = station.trmm.cl3, precipitation = TRUE,  method = "pqm", cross.val = "loo", wt = T)


#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl3.pqm$Dates$start <- as.POSIXct(cal.station.cl3.pqm$Dates$start,tz = "GMT")
cal.station.cl3.pqm$Dates$end <- as.POSIXct(cal.station.cl3.pqm$Dates$end,tz = "GMT")

cal.station.cl4.eqm <- biasCorrection(y = station.obs.cl4, x = station.trmm.cl4, precipitation = TRUE,  method = "eqm", cross.val = "loo", wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl4.eqm$Dates$start <- as.POSIXct(cal.station.cl4.eqm$Dates$start,tz = "GMT")
cal.station.cl4.eqm$Dates$end <- as.POSIXct(cal.station.cl4.eqm$Dates$end,tz = "GMT")

cal.station.cl5.eqm <- biasCorrection(y = station.obs.cl5, x = station.trmm.cl5, precipitation = TRUE,  method = "eqm", cross.val = "loo", wt = T)

#cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = which(!is.na(cal.station.cl1.pqm$Data)))

cal.station.cl5.eqm$Dates$start <- as.POSIXct(cal.station.cl5.eqm$Dates$start,tz = "GMT")
cal.station.cl5.eqm$Dates$end <- as.POSIXct(cal.station.cl5.eqm$Dates$end,tz = "GMT")


idx <- which(!is.na(cal.station.cl1.pqm$Data))
cal.station.cl1.pqm <- subsetDimension(cal.station.cl1.pqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl2.eqm$Data))
cal.station.cl2.eqm <- subsetDimension(cal.station.cl2.eqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl3.pqm$Data))
cal.station.cl3.pqm <- subsetDimension(cal.station.cl3.pqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl4.eqm$Data))
cal.station.cl4.eqm <- subsetDimension(cal.station.cl4.eqm, dimension = "time", indices = idx)

idx <- which(!is.na(cal.station.cl5.eqm$Data))
cal.station.cl5.eqm <- subsetDimension(cal.station.cl5.eqm, dimension = "time", indices = idx)


wt_conditioned <- bindGrid(cal.station.cl1.pqm, cal.station.cl2.eqm, cal.station.cl3.pqm,
                           cal.station.cl4.eqm, cal.station.cl5.eqm, dimension = "time")

attr(wt_conditioned$Data, "dimensions") <- "time"
```
```{r}
cal.station.complete <- biasCorrection(y = station.obs, x = station.trmm, precipitation = TRUE,  method = "pqm", cross.val = "loo")

```


```{r}

# cal.station.complete$Dates$start <- as.POSIXct(cal.station.complete$Dates$start,tz = "GMT")
# cal.station.complete$Dates$end <- as.POSIXct(cal.station.complete$Dates$end,tz = "GMT")

index.combinated <- valueIndex1D(wt_conditioned$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.combinated <- c(index.combinated, valueIndex1D(wt_conditioned$Data[!is.na(wt_conditioned$Data)], index.codes = "P98WetAmount"))

index.combinated.rv20max <- MaxReturnValue(wt_conditioned)

index.combinated <- c(index.combinated, index.combinated.rv20max)

```

```{r}
index.pqm<- valueIndex1D(cal.station.complete$Data,index.codes=c("Skewness","SDII","R10","R10p","R20","R20p","P98Wet"))

index.pqm <- c(index.pqm, valueIndex1D(cal.station.complete$Data[!is.na(cal.station.complete$Data)], index.codes = "P98WetAmount"))

index.pqm.rv20max <- MaxReturnValue(cal.station.complete)
index.pqm<- c(index.pqm ,index.pqm.rv20max)

index.pqm

```
```{r}
diff.conditioned <- abs(index.obs-index.combinated)

diff.pqm <- abs(index.obs-index.pqm)
```


```{r}
measures <- list()
for (i in c(1:9)) {
  measures[[length(measures)+1]] <- c(abs(index.cal.station.pqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.eqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm.complete[i]-index.obs.complete[i]), abs(index.cal.station.gpqm2.complete[i]-index.obs.complete[i]), abs(index.combinated[i]-index.obs.complete[i])) 
}

```

```{r}
norm.vector <- list()
for (i in c(1:length(measures))) {
  norm.vector[[length(norm.vector)+1]] <- normalization(measures[[i]]) 
}
```

```{r}
# score.trmm <- c()
# for (i in c(1:9)) {
#   score.trmm <- c(score.trmm, norm.vector[[i]][1]) 
# }
# score.trmm <- mean(score.trmm)


score.pqm <- c()
for (i in c(1:9)) {
  score.pqm <- c(score.pqm, norm.vector[[i]][1]) 
}
score.pqm <- mean(score.pqm)


score.eqm <- c()
for (i in c(1:9)) {
  score.eqm <- c(score.eqm, norm.vector[[i]][2]) 
}
score.eqm <- mean(score.eqm)


score.gpqm <- c()
for (i in c(1:9)) {
  score.gpqm <- c(score.gpqm, norm.vector[[i]][3]) 
}
score.gpqm <- mean(score.gpqm)



score.gpqm2 <- c()
for (i in c(1:9)) {
  score.gpqm2 <- c(score.gpqm2, norm.vector[[i]][4]) 
}
score.gpqm2 <- mean(score.gpqm2)

score.combinated <- c()
for (i in c(1:9)) {
  score.combinated <- c(score.combinated, norm.vector[[i]][5]) 
}
score.combinated <- mean(score.combinated)

scores <- c(score.pqm, score.eqm, score.gpqm, score.gpqm2, score.combinated)
names(scores) <- c("PQM-C","EQM-C","GPQM-C","GPQM2-C","Combined")
scores <- sort(scores, decreasing = T)
scores
```
```{r}
df <- data.frame(index.obs, index.combinated, index.pqm)

colnames(df) <- c("Observation","Conditioned", "PQM")

format(df, digits = 3, scientific = 5)
```
```{r}
bias.df <- data.frame(diff.conditioned, diff.pqm)

colnames(bias.df) <- c("Bias Conditioned", "Bias PQM")

format(bias.df, digits = 3, scientific = 5)
```

```{r}
df.st1 <- df
bias.df.st1 <- bias.df
```

```{r}
bias.rel.cond <- (abs(df[,2]-df[,1])/df[,1])*100

names(bias.rel.cond) <- names(diff.conditioned)

bias.rel.no.cond <- (abs(df[,3]-df[,1])/df[,1])*100

names(bias.rel.no.cond) <- names(diff.conditioned)
```

```{r}
bias.rel.df <- data.frame(bias.rel.cond, bias.rel.no.cond)

colnames(bias.rel.df) <- c("Relative Bias Conditioned", "Relative Bias PQM")

format(bias.rel.df, digits = 3, scientific = 5)
```


```{r}
qqplot(station.obs$Data, wt_conditioned$Data, main = paste(station.obs$Metadata$name), xlab = "Observed (mm)", ylab = "Predicted (mm)", col = "black", pch = 2, cex = .5, ylim = c(0,500))

abline(a = 0, b = 1)

station.trmm <- subsetDimension(station.trmm, dimension = "time", indices = which(!is.na(station.obs$Data)))

points(sort(station.obs$Data), sort(station.trmm$Data), col = "red", pch = 4, cex = .5)
# points(sort(station.obs$Data[!is.na(station.obs$Data)]), sort(station.trmm$Data[!is.na(station.obs$Data)][-1]), col = "red", pch = 4, cex = .5)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = which(!is.na(station.obs$Data)))

idx <- intersect(which(!is.na(cal.station.complete$Data)),which(!is.na(station.obs$Data)))

station.obs <- subsetDimension(station.obs, dimension = "time", indices = idx)
cal.station.complete <- subsetDimension(cal.station.complete, dimension = "time", indices = idx)

points(sort(station.obs$Data), sort(cal.station.complete$Data), col = "blue", pch = 4, cex = .5)

legend("topleft", legend = c("Combinated","TRMM","EQM"), pch = c(2,4,4), col = c("black", "red","blue"))

grid() 
```